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Manerikar, Ninad. "Fusion de capteurs visuels-inertiels et estimation d'état pour la navigation des véhicules autonomes." Thesis, Université Côte d'Azur, 2022. http://www.theses.fr/2022COAZ4111.
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L’estimation précise de l’état du système est un problème fondamental pour la navigation des véhicules autonomes. Ceci est particulièrement important lorsque le véhicule navigue dans des environnements encombrés ou à proximité d’obstacles, afin d’effectuer la localisation, l’évitement d’obstacles, la cartographie de l’environnement, etc. Bien que plusieurs algorithmes aient été proposés dans le passé pour ce problème d’estimation d’état, ils impliquent généralement un seul capteur ou plusieurs du même type. Afin de pouvoir exploiter les propriétés de multiples capteurs dotés de caractéristiques différentes (tels que Camera, IMU, Lidar, etc.), les chercheurs de la communauté de vision et de contrôle ont mis au point des modèles mathématiques qui produisent des estimations locales précises (position, orientation, vitesse, etc.). En m’inspirant de cela, ma thèse se concentre sur le développement d’observateurs non-linéaires pour l’estimation d’état en exploitant les algorithmes classiques de type Riccati en mettant l’accent sur la fusion de capteurs visuels-inertiels. Dans le cadre de cette thèse, nous utilisons une suite de capteurs à faible coût composée d’une caméra monoculaire et d’une centrale inertielle. Dans le cadre de la vision monoculaire, nous faisons l’hypothèse que la cible est pratiquement plate. Bien que cette hypothèse soit restrictive, les solutions proposées sont pertinentes pour de nombreuses applications dans les domaines de la robotique aérienne, terrestre et sous-marine. Dans ce contexte, deux nouveaux observateurs non linéaires sont proposés, le premier pour l’estimation de l’homographie et le deuxième pour l’estimation de l’attitude partielle, de la vitesse linéaire et de la profondeur. Dans la deuxième partie de la thèse, deux nouveaux observateurs déterministes de Riccati sont proposés pour traiter le problème classique de décomposition d’homographie au lieu de le résoudre image par image comme les approches algébriques traditionnelles. Tous ces travaux sont publiés dans des conférences internationales de haut-niveau. Tous les observateurs proposés ci-dessus font partie de la bibliothèque HomographyLab dont je suis l’un des principaux contributeurs. Cette bibliothèque a été évaluée au niveau TRL 7 (Technology Readiness Level) et est protégée par l’APP (Agence pour la Protection des Programmes) qui sert de brique principale pour diverses applications telles que l’estimation de vitesse et de flux optique, et la stabilisation basée sur l’homographie visuelleAccurate state estimation is a fundamental problem for the navigation of Autonomous vehicles. This is particularly important when the vehicle is navigating through cluttered environments or it has to navigate in close proximity to its physical surroundings in order to perform localization, obstacle avoidance, environmental mapping etc. Although several algorithms were proposed in the past for this problem of state estimtation, they were usually applied to a single sensor or a specific sensor suite. To this end, researchers in the computer vision and control community came up with a visual-inertial framework (Camera + Imu) that exploit the combined properties of this sensor suite to produce precise local estimates (position, orientation, velocity etc). Taking inspiration from this, my thesis focuses on developing nonlinear observers for State Estimation by exploiting the classical Riccati design framework with a particular emphasis on visual-inertial sensor fusion. In the context of this thesis, we use a suite of low-cost sensors consisting of a monocular camera and an IMU. Throughout the thesis, the assumption on the planarity of the visual target has been considered. In the present thesis, two research topics have been considered. Firstly, an extensive study for the existing techniques for homography estimation has been carried out after which a novel nonlinear observer on the SL(3) group has been proposed with application to optical flow estimation. The novelty lies in the linearization approach undertaken to linearize a nonlinear observer on SL(3), thus making it more simplistic and suitable for practical implementation. Then, another novel observer based on deterministic Ricatti observer has been proposed for the problem of partial attitude, linear velocity and depth estimation for planar targets. The proposed approach does not rely on the strong assumption that the IMU provides the measurements of the vehicle’s linear acceleration in the body-fixed frame. Again experimental validations have been carried out to show the performance of the observer. An extension to this observer has been further proposed to filter the noisy optical flow estimates obtained from the extraction of continuous homography. Secondly, two novel observers for tackling the classical problem of homography decomposition have been proposed. The key contribution here lies in the design of two deterministic Riccati observers for addressing the homography decomposition problem instead of solving it on a frame-by-frame basis like traditional algebraic approaches. The performance and robustness of the observers have been validated over simulations and practical experiments. All the observers proposed above are part of the Homography-Lab library that has been evaluated at the TRL 7 (Technology Readiness Level) and is protected by the French APP (Agency for the Protection of Programs) which serves as the main brick for various applications like velocity, optical flow estimation and visual homography based stabilization
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DiMascio, Michelle Augustine. "Convolutional Neural Network Optimization for Homography Estimation." University of Dayton / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1544214038882564.
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Zeng, Rui. "Homography estimation: From geometry to deep learning." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/134132/1/Rui_Zeng_Thesis.pdf.
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Homography is an important area of computer vision for scene understanding and plays a key role in extracting relationships across different viewpoints of a scene. This thesis focuses on studying homography transformations between images from both geometric and deep learning perspectives. We have developed an accurate and effective homography estimation system for sports scenes analysis an efficient and novel 3D perspective feature to improve 3D object recognition especially for the vehicle recognition.
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Turk, Matthew Robert. "A homography-based multiple-camera person-tracking algorithm /." Online version of thesis, 2008. http://hdl.handle.net/1850/7853.
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Graham, Athelia. "The Effects of Homography on Computer-generated High Frequency Word Lists." Diss., CLICK HERE for online access, 2008. http://contentdm.lib.byu.edu/ETD/image/etd2692.pdf.
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Fristedt, Hampus. "Homography Estimation using Deep Learning for Registering All-22 Football Video Frames." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-209583.
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Homography estimation is a fundamental task in many computer vision applications, but many techniques for estimation rely on complicated feature extraction pipelines. We extend research in direct homography estimation (i.e. without explicit feature extraction) by implementing a convolutional network capable of estimating homographies. Previous work in deep learning based homography estimation calculates homographies between pairs of images, whereas our network takes single image input and registers it to a reference view where no image data is available. The application of the work is registering frames from American football video to a top-down view of the field. Our model manages to register frames in a test set with an average corner error equivalent to less than 2 yards.Homografiuppskattning är ett förkrav för många problem inom datorseende, men många tekniker för att uppskatta homografier bygger på komplicerade processer för att extrahera särdrag mellan bilderna. Vi bygger på tidigare forskning inom direkt homografiuppskattning (alltså, utan att explicit extrahera särdrag) genom att implementera ett Convolutional Neural Network (CNN) kapabelt av att direkt uppskatta homografier. Arbetet tillämpas för att registrera bilder från video av amerikansk fotball till en referensvy av fotbollsplanen. Vår modell registrerar bildramer från ett testset till referensvyn med ett snittfel i bildens hörn ekvivalent med knappt 2 yards.
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Ähdel, Victor. "On the effect of architecture on deep learning based features for homography estimation." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233194.
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Keypoint detection and description is the first step of homography and essential matrix estimation, which in turn is used in Visual Odometry and Visual SLAM. This work explores the effect (in terms of speed and accuracy) of using different deep learning architectures for such keypoints. The fully convolutional networks — with heads for both the detector and descriptor — are trained through an existing self-supervised method, where correspondences are obtained through known randomly sampled homographies. A new strategy for choosing negative correspondences for the descriptor loss is presented, which enables more flexibility in the architecture design. The new strategy turns out to be essential as it enables networks that outperform the learnt baseline at no cost in inference time. Varying the model size leads to a trade-off in speed and accuracy, and while all models outperform ORB in homography estimation, only the larger models approach SIFT’s performance; performing about 1-7% worse. Training for longer and with additional types of data might give the push needed to outperform SIFT. While the smallest models are 3× faster and use 50× fewer parameters than the learnt baseline, they still require 3× as much time as SIFT while performing about 10-30% worse. However, there is still room for improvement through optimization methods that go beyond architecture modification, e.g. quantization, which might make the method faster than SIFT.Nyckelpunkts-detektion och deskriptor-skapande är det första steget av homografi och essentiell matris estimering, vilket i sin tur används inom Visuell Odometri och Visuell SLAM. Det här arbetet utforskar effekten (i form av snabbhet och exakthet) av användandet av olika djupinlärnings-arkitekturer för sådana nyckelpunkter. De hel-faltade nätverken – med huvuden för både detektorn och deskriptorn – tränas genom en existerande själv-handledd metod, där korrespondenser fås genom kända slumpmässigt valda homografier. En ny strategi för valet av negativa korrespondenser för deskriptorns träning presenteras, vilket möjliggör mer flexibilitet i designen av arkitektur. Den nya strategin visar sig vara väsentlig då den möjliggör nätverk som presterar bättre än den lärda baslinjen utan någon kostnad i inferenstid. Varieringen av modellstorleken leder till en kompromiss mellan snabbhet och exakthet, och medan alla modellerna presterar bättre än ORB i homografi-estimering, så är det endast de större modellerna som närmar sig SIFTs prestanda; där de presterar 1-7% sämre. Att träna längre och med ytterligare typer av data kanske ger tillräcklig förbättring för att prestera bättre än SIFT. Även fast de minsta modellerna är 3× snabbare och använder 50× färre parametrar än den lärda baslinjen, så kräver de fortfarande 3× så mycket tid som SIFT medan de presterar runt 10-30% sämre. Men det finns fortfarande utrymme för förbättring genom optimeringsmetoder som övergränsar ändringar av arkitekturen, som till exempel kvantisering, vilket skulle kunna göra metoden snabbare än SIFT.
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Kio, Onoise Gerald. "Distortion correction for non-planar deformable projection displays through homography shaping and projected image warping." Thesis, University of Central Lancashire, 2016. http://clok.uclan.ac.uk/16569/.
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Video projectors have advanced from being tools for only delivering presentations on flat or planar surfaces to tools for delivering media content in such applications as augmented reality, simulated sports practice and invisible displays. With the use of non-planar surfaces for projection comes geometric and radiometric distortions. This work dwells on correcting geometric distortions occurring when images or video frames are projected onto static and deformable non-planar display surfaces. The distortion-correction process involves (i) detecting feature points from the camera images and creating a desired shape of the undistorted view through a 2D homography, (ii) transforming the feature points on the camera images to control points on the projected images, (iii) calculating Radial Basis Function (RBF) warping coefficients from the control points, and warping the projected image to obtain an undistorted image of the projection on the projection surface. Several novel aspects of this work have emerged and include (i) developing a theoretical framework that explains the cause of distortion and provides a general warping pattern to be applied to the projection, (ii) carrying out the distortion-correction process without the use of a distortion-measuring calibration image or structured light pattern, (iii) carrying out the distortioncorrection process on a projection display that deforms with time with a single uncalibrated projector and uncalibrated camera, and (iv) performing an optimisation of the distortioncorrection processes to operate in real-time. The geometric distortion correction process designed in this work has been tested for both static projection systems in which the components remain fixed in position, and dynamic projection systems in which the positions of components or shape of the display change with time. The results of these tests show that the geometric distortion-correction technique developed in this work improves the observed image geometry by as much as 31% based on normalised correlation measure. The optimisation of the distortion-correction process resulted in a 98% improvement of its speed of operation thereby demonstrating the applicability of the proposed approach to real projection systems with deformable projection displays.
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Bazargani, Hamid. "Real-Time Recognition of Planar Targets on Mobile Devices. A Framework for Fast and Robust Homography Estimation." Thesis, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31698.
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The present thesis is concerned with the problem of robust pose estimation for planar targets in the context of real-time mobile vision. As a consequence of this research, individual developments made in isolation by earlier researchers are here considered together.
Several adaptations to the existing algorithms are undertaken yielding a unified framework for robust pose estimation. This framework is specifically designed to meet the growing demand for fast and robust estimation on power-constrained platforms.
For robust recognition of targets at very low computational costs, we employ feature based methods which are based on local binary descriptors allowing fast feature matching at run-time. The matching set is then fed to a robust parameter estimation algorithm in order to obtain a reliable homography. On the basis of our experimental results, it can be concluded that reliable homography estimates can be obtained using a device-friendly implementation of the Gaussian Elimination algorithm. We also show in this thesis that our simplified approach can significantly improve the homography estimation step in a hypothesize-and-verify scheme. The author's attention is focused not only on developing fast algorithms for the recognition framework but also on the optimized implementation of such algorithms. Any other recognition framework would similarly benefit from our optimized implementation.
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Xu, Jun [Verfasser]. "A Textile Fabric Protruding Fibers Measurement System Based on Camera Vision and Variable Homography / Jun Xu." Düren : Shaker, 2019. http://d-nb.info/119052600X/34.
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Du, Ruixiang. "An Intelligent Portable Aerial Surveillance System: Modeling and Image Stitching." Digital WPI, 2013. https://digitalcommons.wpi.edu/etd-theses/859.
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"Unmanned Aerial Vehicles (UAVs) have been widely used in modern warfare for surveillance, reconnaissance and even attack missions. They can provide valuable battlefield information and accomplish dangerous tasks with minimal risk of loss of lives and personal injuries. However, existing UAV systems are far from perfect to meet all possible situations. One of the most notable situations is the support for individual troops. Besides the incapability to always provide images in desired resolution, currently available systems are either too expensive for large-scale deployment or too heavy and complex for a single solder. Intelligent Portable Aerial Surveillance System (IPASS), sponsored by the Air Force Research Laboratory (AFRL), is aimed at developing a low-cost, light-weight unmanned aerial vehicle that can provide sufficient battlefield intelligence for individual troops. The main contributions of this thesis are two-fold (1) the development and verification of a model-based flight simulation for the aircraft, (2) comparison of image stitching techniques to provide a comprehensive aerial surveillance information from multiple vision. To assist with the design and control of the aircraft, dynamical models are established at different complexity levels. Simulations with these models are implemented in Matlab to study the dynamical characteristics of the aircraft. Aerial images acquired from the three onboard cameras are processed after getting the flying platform built. How a particular image is formed from a camera and the general pipeline of the feature-based image stitching method are first introduced in the thesis. To better satisfy the needs of this application, a homography-based stitching method is studied. This method can greatly reduce computation time with very little compromise in the quality of the panorama, which makes real-time video display of the surroundings on the ground station possible. By implementing both of the methods for image stitching using OpenCV, a quantitative comparison in the performance is accomplished."
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Sanders, Larry Dean Jr. "IR Illumination-Assisted Smart Headlight Glare Reduction." University of Dayton / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=dayton151211742430073.
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Ebdelli, Mounira. "Video inpainting techniques : application to object removal and error concealment." Thesis, Rennes 1, 2014. http://www.theses.fr/2014REN1S092/document.
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Cette thèse présente des outils de vidéo inpainting permettant de reconstruire de manière efficace les zones perdues d'une séquence vidéo. Deux catégories d'approches sont particulièrement étudiées. Dans une première étape les approches basées sur l'exemple sont considérées. Différentes contributions ont été proposées. Une application des méthodes de neighbor embedding pour l'approximation des pixels perdus dans un exemple est d'abord considérée en utilisant deux méthodes de réduction de dimensionnalité: la factorisation de matrice non négative (FMN) et le locally linear embedding (LLE). La méthode d'inpainting proposée a été ensuite adaptée à l'application de dissimulation d'erreurs en utilisant une étape de pré-traitement d'estimation des vecteurs de mouvement perdus. Une approche multisolution a également été considérée pour réduire la complexité. Les évaluations expérimentales de cette approche démontrent son efficacité dans les applications de suppression d'objets et de dissimulation des erreurs. Une deuxième catégorie de méthodes de vidéo inpaintinting a été par la suite étudiée en utilisant une approche basée sur l'optimisation globale d'une fonction d'énergie exprimant la cohérence spatio-temporelle de la région reconstruite. Enfin, le problème d'inpainting des vidéos capturées par des caméras en mouvement a été étudié. L'alignement des images en utilisant une homographie par région montre de meilleure performances que les méthodes classiques d'alignement par optimisation d'une homography par pixelThis thesis presents video inpainting tools to efficiently recover space-time holes in different kinds of video sequences. Two categories of video inpainting approaches are particularly studied. The first category concerns exemplar-based approach. Several contributions have been proposed for this approach. Neighbor embedding techniques have been proposed for patch sampling using two data dimensionality reductions methods: non-negative matrix factorization (NMF) and locally linear embedding (LLE). An analysis of similarity metrics for patches matching have then been proposed based on both subjective and objective tests. The proposed framework have been also adapted to the error concealment application by using a preprocessing step of motion estimation. A multiresolution approach has been considered to reduce the computational time of the method. The experimental evaluations demonstrate the effectiveness of the proposed video inpainting approach in both object removal and error concealment applications. The video inpainting problem has been also solved using a second approach based on the optimization of a well-defined cost function expressing the global consistency of the recovered regions. The camera moving videos has later been takled by using a region-based homography. The neighboring frames in the sequence are aligned based on segmented planar regions. This method has been shown to give better performance compared to classical optimization-based homography
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Pouladzadeh, Parvaneh. "Design and Implementation of Video View Synthesis for the Cloud." Thesis, Université d'Ottawa / University of Ottawa, 2017. http://hdl.handle.net/10393/37048.
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In multi-view video applications, view synthesis is a computationally intensive task that needs to be done correctly and efficiently in order to deliver a seamless user experience. In order to provide fast and efficient view synthesis, in this thesis, we present a cloud-based implementation that will be especially beneficial to mobile users whose devices may not be powerful enough for high quality view synthesis. Our proposed implementation balances the view synthesis algorithm’s components across multiple threads and utilizes the computational capacity of modern CPUs for faster and higher quality view synthesis. For arbitrary view generation, we utilize the depth map of the scene from the cameras’ viewpoint and estimate the depth information conceived from the virtual camera. The estimated depth is then used in a backward direction to warp the cameras’ image onto the virtual view. Finally, we use a depth-aided inpainting strategy for the rendering step to reduce the effect of disocclusion regions (holes) and to paint the missing pixels. For our cloud implementation, we employed an automatic scaling feature to offer elasticity in
order to adapt the service load according to the fluctuating user demands. Our performance results using 4 multi-view videos over 2 different scenarios show that our proposed system achieves average improvement of 3x speedup, 87% efficiency, and 90% CPU utilization for the parallelizable parts of the algorithm.
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Nott, Viswajith Karapoondi. "Joint Visual and Wireless Tracking System." UKnowledge, 2009. http://uknowledge.uky.edu/gradschool_theses/592.
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Object tracking is an important component in many applications including surveillance, manufacturing, inventory tracking, etc. The most common approach is to combine a surveillance camera with an appearance-based visual tracking algorithm. While this approach can provide high tracking accuracy, the tracker can easily diverge in environments where there are much occlusions. In recent years, wireless tracking systems based on different frequency ranges are becoming more popular. While systems using ultra-wideband frequencies suffer similar problems as visual systems, there are systems that use frequencies as low as in those in the AM band to circumvent the problems of obstacles, and exploit the near-field properties between the electric and magnetic waves to achieve tracking accuracy down to about one meter. In this dissertation, I study the combination of a visual tracker and a low-frequency wireless tracker to improve visual tracking in highly occluded area. The proposed system utilizes two homographies formed between the world coordinates with the image coordinates of the head and the foot of the target person. Using the world coordinate system, the proposed system combines a visual tracker and a wireless tracker in an Extended Kalman Filter framework for joint tracking. Extensive experiments have been conducted using both simulations and real videos to demonstrate the validity of our proposed scheme.
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Lai, Po-Lun. "Shape Recovery by Exploiting Planar Topology in 3D Projective Space." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1268187247.
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Fenimore, Carson D. "A Foveated System for Wilderness Search and Rescue in Manned Aircraft." BYU ScholarsArchive, 2011. https://scholarsarchive.byu.edu/etd/2744.
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Wilderness search and rescue can be assisted by video searchers in manned aircraft. The video searcher's primary task is to find clues on the ground. Due to altitude, it may be difficult to resolve details on the ground with a standard video camera. As the video streams at a constant frame rate, the searcher may become distracted by other tasks. While handling these tasks the searcher may miss important clues or spend extra time flying over the search area; either outcome decreases both the effectiveness of the video searcher and the chances of successfully finding missing persons. We develop an efficient software system that allows the video searcher to deal with distractions while identifying, resolving, and geolocating clues using mixed-resolution video. We construct an inexpensive camera rig that feeds video and telemetry to this system. We also develop a simple flight simulator for generating synthetic search video for simulation and testing purposes. To validate our methods we conduct a user study and a field trial. An analysis of the user study results suggests that our system can combine the video streams without loss of performance in the primary or secondary search task. The resulting gains in screen-space efficiency can then be used to present more information, such as scene context or larger-resolution images. Additionally, the field trial suggests that the software is capable of robustly operating in a real-world environment.
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Jansson, Ludvig. "Automatic Matching of Multimodular Images in Live Golf Environments : An Evaluation of Methods to Estimate a Homography Between Multimodular Images." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-190747.
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This degree project evaluates combinations of well-known state-of-the-art keypoint detectors and descriptors, as well as keypoint matching and robust outlier rejection methods for the purpose of estimating a homography between images produced by two fundamentally different cameras. The evaluation is perfomed on both computational efficiency and matching accuracy of each combination after a series of image deformations have been applied. The results show best performance using Brute Force search with the Hamming distance on keypoint descriptors generated by running the BRISK/BRISK combination and RANSAC for finding the subset to be used in the final homography estimation. If necessary for extra time sensitive applications, using ORB/ORB for keypoint detection and description has been shown to produce largely comparable results at a higher computational efficiencyDet här arbetet evaluerar kombinationer av välkända detektorer och deskriptorer, samt metoder för att matcha dessa och välja ut de bästa för att estimera en homografi mellan två fundamentalt olika kameror. Evalueringen baseras både på tidsåtgång och slutgiltig matchningskvalitet efter en rad bilddeformationer har applicerats. Resultaten visar bäst resultat när en totalsökning med Hammingnormen körs på ett set av punkter funna med hjälp av kombinationen BRISK/BRISK och sedan RANSAC för att hitta det bästa subsetet av dessa för att estimera homografin. Om nödvändigt för extra tidskänsliga applikationer har kombinationen ORB/ORB visat sig prestera i stort sett lika bra och med en ökad effektivitet.
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Lewis, Benjamin Paul. "A Visual Return-to-Home System for GPS-Denied Flight." BYU ScholarsArchive, 2016. https://scholarsarchive.byu.edu/etd/6254.
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Unmanned aerial vehicle technology is rapidly maturing. In recent years, the sight of hobbyist aircraft has become more common. Corporations and governments are also interested in using drone aircraft for applications such as package delivery, surveillance and communications. These autonomous UAV technologies demand robust systems that perform under any circumstances. Many UAV applications rely on GPS to obtain information about their location and velocity. However, the GPS system has known vulnerabilities, including environmental signal degradation, terrestrial or solar weather, or malicious attacks such as GPS spoofing. These conditions occur with enough frequency to cause concern. Without a GPS signal, the state estimation in many autopilots quickly degrades. In the absence of a reliable backup navigation scheme, this loss of state will cause the aircraft to drift off course, and in many cases the aircraft will lose power or crash. While no single approach can solve all of the issues with GPS signal degradation, individual events can be addressed and solved. In this thesis, we present a system which will return an aircraft to its launch point upon the loss of GPS. This functionality is advantageous because it allows recovery of the UAV in circumstances which the lack of GPS information would make difficult. The system presented in this thesis accomplishes the return of the aircraft by means of onboard visual navigation, which removes the dependence of the aircraft on external sensors and systems. The system presented here uses an downward-facing onboard camera and computer to capture a string of overlapping images (keyframes) of the ground as the aircraft travels on its outbound journey. When a signal is received, the aircraft switches into return-to-home mode. The system uses the homography matrix and other vision processing techniques to produce information about the location of the current keyframe relative to the aircraft. This information is used to navigate the aircraft to the location of each saved keyframe in reverse order. As each keyframe is reached, the system programmatically loads the next target keyframe. By following the chain of keyframes in reverse, the system reaches the launch location. Contributions in this thesis include the return-to-home visual flight system for UAVs, which has been tested in simulation and with flight tests. Features of this system include methods for determining new keyframes and switching keyframes on the inbound flight, extracting data between images, and flight navigation based on this information. This system is a piece of the wider GPS-denied framework under development in the BYU MAGICC lab.
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Rydström, Daniel. "Calibration of Laser Triangulating Cameras in Small Fields of View." Thesis, Linköpings universitet, Datorseende, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-94210.
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A laser triangulating camera system projects a laser line onto an object to create height curveson the object surface. By moving the object, height curves from different parts of the objectcan be observed and combined to produce a three dimensional representation of the object.The calibration of such a camera system involves transforming received data to get real worldmeasurements instead of pixel based measurements. The calibration method presented in this thesis focuses specifically on small fields ofview. The goal is to provide an easy to use and robust calibration method that can complementalready existing calibration methods. The tool should get as good measurementsin metric units as possible, while still keeping complexity and production costs of the calibrationobject low. The implementation uses only data from the laser plane itself making itusable also in environments where no external light exist. The proposed implementation utilises a complete scan of a three dimensional calibrationobject and returns a calibration for three dimensions. The results of the calibration havebeen evaluated against synthetic and real data.
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Rosenquist, Calle, and Andreas Evesson. "Visual Servoing In Semi-Structured Outdoor Environments." Thesis, Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-653.
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The field of autonomous vehicle navigation and localization is a highly active research
topic. The aim of this thesis is to evaluate the feasibility to use outdoor visual navigation in a semi-structured environment. The goal is to develop a visual navigation system for an autonomous golf ball collection vehicle operating on driving ranges.
The image feature extractors SIFT and PCA-SIFT was evaluated on an image database
consisting of images acquired from 19 outdoor locations over a period of several weeks to
allow different environmental conditions. The results from these tests show that SIFT-type
feature extractors are able to find and match image features with high accuracy. The results also show that this can be improved further by a combination of a lower nearest neighbour threshold and an outlier rejection method to allow more matches and a higher ratio of correct matches. Outliers were found and rejected by fitting the data to a homography model with the RANSAC robust estimator algorithm.
A simulator was developed to evaluate the suggested system with respect to pixel noise from illumination changes, weather and feature position accuracy as well as the distance to features, path shapes and the visual servoing target image (milestone) interval. The system was evaluated on a total of 3 paths, 40 test combinations and 137km driven. The results show that with the relatively simple visual servoing navigation system it is possible to use mono-vision as a sole sensor and navigate semi-structured outdoor environments such as driving ranges.
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Andersson, Robert. "A calibration method for laser-triangulating 3D cameras." Thesis, Linköping University, Department of Electrical Engineering, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-15735.
Full textAbstract:
A laser-triangulating range camera uses a laser plane to light an object. If the position of the laser relative to the camera as well as certrain properties of the camera is known, it is possible to calculate the coordinates for all points along the profile of the object. If either the object or the camera and laser has a known motion, it is possible to combine several measurements to get a three-dimensional view of the object.
Camera calibration is the process of finding the properties of the camera and enough information about the setup so that the desired coordinates can be calculated. Several methods for camera calibration exist, but this thesis proposes a new method that has the advantages that the objects needed are relatively inexpensive and that only objects in the laser plane need to be observed. Each part of the method is given a thorough description. Several mathematical derivations have also been added as appendices for completeness.
The proposed method is tested using both synthetic and real data. The results show that the method is suitable even when high accuracy is needed. A few suggestions are also made about how the method can be improved further.
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Kaba, Utku. "Moving Hot Object Detection In Airborne Thermal Videos." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614532/index.pdf.
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In this thesis, we present an algorithm for vision based detection of moving objects observed by IR sensors on a moving platform. In addition we analyze the performance of different approaches in each step of the algorithm. The proposed algorithm is composed of preprocessing, feature detection, feature matching, homography estimation and difference image analysis steps. First, a global motion estimation based on planar homography model is performed in order to compensate the motion of the sensor and moving platform where the sensors are located. Then, moving objects are identified on difference images of consecutive video frames with global motion suppression. Performance of the proposed algorithm is shown on different IR image sequences.
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Björkeson, Felix. "Autonomous Morphometrics using Depth Cameras for Object Classification and Identification." Thesis, Linköpings universitet, Datorseende, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-95240.
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Identification of individuals has been solved with many different solutions around the world, either using biometric data or external means of verification such as id cards or RFID tags. The advantage of using biometric measurements is that they are directly tied to the individual and are usually unalterable. Acquiring dependable measurements is however challenging when the individuals are uncooperative. A dependable system should be able to deal with this and produce reliable identifications. The system proposed in this thesis can autonomously classify uncooperative specimens from depth data. The data is acquired from a depth camera mounted in an uncontrolled environment, where it was allowed to continuously record for two weeks. This requires stable data extraction and normalization algorithms to produce good representations of the specimens. Robust descriptors can therefore be extracted from each sample of a specimen and together with different classification algorithms, the system can be trained or validated. Even with as many as 138 different classes the system achieves high recognition rates. Inspired by the research field of face recognition, the best classification algorithm, the method of fisherfaces, was able to accurately recognize 99.6% of the validation samples. Followed by two variations of the method of eigenfaces, achieving recognition rates of 98.8% and 97.9%. These results affirm that the capabilities of the system are adequate for a commercial implementation.
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DeFranco, Patrick. "Detecting and Tracking Moving Objects from a Small Unmanned Air Vehicle." BYU ScholarsArchive, 2015. https://scholarsarchive.byu.edu/etd/5311.
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As the market for unmanned air vehicles (UAVs) rapidly expands, the need for algorithmsthat improve the capabilities of those vehicles is also growing. One valuable capability for UAVsis that of persistent tracking—the ability to find and track another moving object, usually on theground, from an aerial platform. This thesis presents a method for tracking multiple ground targetsfrom an airborne camera. Moving objects on the ground are detected by using frame-to-frameregistration. The detected objects are then tracked using the newly developed recursive RANSACalgorithm. Much video tracking work has focused on using appearance-based processing for tracking,with some approaches using dynamic trackers such as Kalman filters. This work demonstratesa fusion of computer vision and dynamic tracking to increase the ability of an unmanned air platformto identify and robustly track moving targets. With a C++ implementation of the algorithmsrunning on the open source Robot Operating System (ROS) framework, the system developed iscapable of processing 1920x1080 resolution video at over seven frames per second on a desktopcomputer.
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Jurzykowski, Michal. "Eye Tracking in User Interfaces." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2012. http://www.nusl.cz/ntk/nusl-236489.
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Tato diplomová práce byla vytvořena během studijního pobytu na Uviversity of Estern Finland, Joensuu, Finsko. Tato diplomová práce se zabývá využitím technologie sledování pohledu neboli také sledování pohybu očí (Eye-Tracking) pro interakci člověk-počítač (Human-Computer Interaction (HCI)). Navržený a realizovaný systém mapuje pozici bodu pohledu/zájmu (the point of gaze), která odpovídá souřadnicím v souřadnicovém systému kamery scény do souřadnicového systému displeje. Zároveň tento systém kompenzuje pohyby uživatele a tím odstraňuje jeden z hlavních problémů využití sledování pohledu v HCI. Toho je dosaženo díky stanovení transformace mezi projektivním prostorem scény a projektivním prostorem displeje. Za použití význačných bodů (interesting points), které jsou nalezeny a popsány pomocí metody SURF, vyhledání a spárování korespondujících bodů a vypočítání homografie. Systém byl testován s využitím testovacích bodů, které byly rozložené po celé ploše displeje.
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Ahmadli, Ismayil. "Interpretation of the user interface of a domestic appliance using robotic vision." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019.
Find full textAbstract:
This master thesis is a part of the project which is conducted by Prof.Gianluca Palli in
cooperation with a private company in Laboratory of Automation and Robotics (LAR) of
the University of Bologna. The project aims to control the given washing machines in a
laundromat using mobile based manipulator and visualize all information in a compared
manner for the user.
The first goal of this thesis is to interpret data on the user interface of the washing
machine using Deep Learning and compare it with actual data acquired from the machine
itself. The focus lies on visualizing these two type of information directly to the user
with the result of this comparison on GUI application. The second goal is to detect the
washing machine and its pieces in certain area using convolutional neural networks.
Deep learning has absolutely dominated computer vision over the last few years,
achieving top score on many task in this field, with neural networks repeatedly push-
ing the frontier of visual recognition.
After introduction basic information about Deep Learning and particularly MobileNet
architectures, Image Processing and Computer Vision concepts are presented. These
concepts such as Homography matrix estimation, are used to automatically localize the
region of interests of the user interface on the scene frame without using any external
markers and recognize the washing program, option and functionalities as well with help
of OpenCV library.
Next, training and validation procedures of MobileNetV2 for both visual recognition
and object detection tasks are described. The results are shown after finetuning with
sample data using TF-Slim image recognition library and training the network for object
detection using Tensorflow’s Object Detection API.
Finally, Loss function on training and validation are indicated and the results on the
scene frame visually are shown in a systematical way and further possible application are
briefly discussed.
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Fransson, Simon. "Mosaicing of Fetoscopic Acquired Images using SIFT and FAST." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-215705.
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This is a study exploring how robust one feature descriptors, scale invariant feature transform (SIFT), and one feature detector, feature accelerated segmentation test (FAST), are in terms of handling fetoscopic acquired data when mosaicing. Today’s treatment of severe Twin-to-Twin Transfusion Syndrome at Karolinska University Hospital is fetoscopic guided laser occlusion of chorioangiopagous vessels (FLOC) where intersecting blood vessels causing a transfusion (Anastomoses) in between the fetuses are occluded. These blood vessels are located somewhere on the placenta. The fetoscopy includes navigation of a relatively large area where the field of view (FOV) is limited. The limited FOV during the fetoscopy makes it cumbersome to navigate and identify intersected blood vessels. The motivation of this study is to explore ways of dealing with the complications during FLOC by mosaicing an overview of the placenta that can be used as an assisting map to make the procedure safer by improving navigation of the fetoscope and identification of blood vessels during FLOC. In this study, the steps of mosaicing are defined based on mosaicing frameworks to explore how these methods perform in terms of being able to mosaic a map of the placenta. The methods have been tested on non-fetoscopic acquired data as well as fetoscopic acquired data to create a relative measure in between the two. Three tests on non- fetoscopic data were performed to explore how well the methods handled mosaicing of data with distinctive characteristics. The same methods were then tested on unprocessed fetoscopic data before being tested on preprocessed fetoscopic data to see if the results were affected by external preprocessing. The results showed that there were differences in between the methods. SIFT and FAST showed that they have potential of mosaicing non-fetoscopic data of varying extent. SIFT gave an impression of being more robust during all of the tests. SIFT especially performed better during the tests on data with few potential keypoints which is an advantage when speaking of fetoscopic acquired data. SIFT also managed to mosaic a larger area than FAST when mosaicing preprocessed fetoscopic data. Preprocessing the data improved the mosaicing when using SIFT but further improvements are needed.Denna studie utforskar hur robust en intressepunktsbeskrivare, scale invariant feature transform (SIFT), och enintressepunktsdetektor, feature accelerated segmentation test (FAST), hanterar digitala bilder insamlade av ett fetoskop med syfte att sy ihop dessa till en översiktskarta. Dagens behandling av tvillingtransfusionsyndrom vid Karolinska Universitetssjukhuset är fetoscopic guided laser occlusion of chorioangiopagous vessels (FLOC). Under denna fetoskopi bränner man och därmed blockerar korsande blodkärl som orsakar en transfusion (anastomoses) och obalans i blodomloppet mellan två tvillingfoster. Dessa blodkärl är lokaliserade på placentan. Fetoskopin omfattar navigering av en relativt stor area med ett begränsat synfält. Det begränsade synfältet under FLOC gör det svårt att orientera fetoskopet och identifiera korsande blodkärl som orsakar transfusionen. Syftet med studien är att utforska ett sätt att hantera komplikationerna med FLOC igenom att utforska sätt att skapa en översiktskarta av placentan under FLOC. Denna översiktskarta kan nyttjas under FLOC och därmed göra proceduren säkrare igenom att kartan underlättar orienteringen av fetoskopet och identifiering av orsakande blodkärl. I denna studie är stegen för att skapa en översiktskarta baserade på olika datorseende ramverk för att se hur dessa tillvägagångssätt presterar när det gäller att skapa en översiktskarta. Metoderna för att skapa en översiktskarta har testats på data insamlad med webkamera och data insamlad med fetoskop för att skapa en relativ uppfattning om hur de står sig beroende på indata. Tre tester på data insamlad med webkamera genomfördes för att utforska hur väl metoderna hanterade data med många potentiella intressepunkter, rörelse orsakad av handhållen enhet/kamera, repetitiva mönster, översiktskartor som resulterande i större upplösning, och liten möjlighet att hitta intressepunkter. Samma metoder testades sedan på icke behandlad data insamlad med fetoskop innan den testades på förbehandlad data insamlad med fetoskop för att se förbehandlingensnödvändighet och prestation. Resultaten visar att det är skillnader mellan de två metoderna använda i denna studie, både när det gäller data insamlad med fetoskop och webkamera. SIFT och FAST visar potential av olika grad när det gäller att skapa en översiktskarta med data insamlad av webkamera. SIFT visade sig vara mer robust under alla tester inklusive data insamlad med fetoskop. SIFT presterade speciellt bättre under testen som omfattade få antal möjliga intressepunkter vilket är en fördel när det gäller data insamlad med fetoskop. SIFT lyckades också skapa översiktskartor med större area än FAST när förbehandlad fetoskopisk data testades. När det gäller SIFT så visade resultaten en förbättring när data insamlad med fetoskop förbehandlades men att ytterligare förbättringar är nödvändiga.
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Ready, Bryce Benson. "Filtering Techniques for Pose Estimation with Applications to Unmanned Air Vehicles." BYU ScholarsArchive, 2012. https://scholarsarchive.byu.edu/etd/3490.
Full textAbstract:
This work presents two novel methods of estimating the state of a dynamic system in a Kalman Filtering framework. The first is an application specific method for use with systems performing Visual Odometry in a mostly planar scene. Because a Visual Odometry method inherently provides relative information about the pose of a platform, we use this system as part of the time update in a Kalman Filtering framework, and develop a novel way to propagate the uncertainty of the pose through this time update method. Our initial results show that this method is able to reduce localization error significantly with respect to pure INS time update, limiting drift in our test system to around 30 meters for tens of seconds. The second key contribution of this work is the Manifold EKF, a generalized version of the Extended Kalman Filter which is explicitly designed to estimate manifold-valued states. This filter works for a large number of commonly useful manifolds, and may have applications to other manifolds as well. In our tests, the Manifold EKF demonstrated significant advantages in terms of consistency when compared to other filtering methods. We feel that these promising initial results merit further study of the Manifold EKF, related filters, and their properties.
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Bjering, Beatrice. "Estimations of 3D velocities from a single camera view in ice hockey." Thesis, KTH, Skolan för kemi, bioteknologi och hälsa (CBH), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254320.
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Ice hockey is a contact sport with a high risk of brain injuries such as concussions. This is a serious health concern and there is a need of better understanding of the relationship between the kinematics of the head and concussions. The velocity and the direction of impact are factors that might affect the severity of the concussions. Therefore the understanding of concussions can be improved by extracting velocities from video analysis. In this thesis a prototype to extract 3D velocities from one single camera view was developed by using target tracking algorithms and homography. A validation of the method was done where the mean error was estimated to 21.7%. The prototype evaluated 60 cases of tackles where 30 resulted in concussions and the other 30 tackles did not result in concussions. No significant difference in the velocities between the two groups could be found. The mean velocity for the tackles that resulted in concussions were 6.55 m/s for the attacking player and 4.59 m/s for the injured player. The prototype was also compared with velocities extracted through SkillSpector from a previous bachelor thesis. There was a significant difference between the velocities compiled with SkillSpector and the developed prototype in this thesis. A validation of SkillSpector was also made, which showed that it had a mean error of 37.4%.Ishockey är en kontaktsport med hög risk för hjärnskador, så som hjärnskakningar. Detta är ett stort hälsoproblem och det finns ett behov av större förståelse mellan huvudets kinematik och hjärnskakningar. Hastigheten och riktningen av kollisionerna är faktorer som kan påverka svårighetsgraden av hjärnskakningarna. Därför kan förståelsen av hjärnskakningar förbättras genom att extrahera hastigheter med videoanalys. I denna rapport utvecklades en prototyp för att ta fram 3D hastigheter från en kameravinkel genom att använda målsökningsalgoritmer och homografi. En validering av prototypen gjordes där medelfelet uppskattades till 21.7%. Prototypen utvärderade även 60 fall av tacklingar där 30 resulterade hjärnskakningar och där de andra 30 tacklingarna inte resulterade i hjärnskakningar. Ingen signifikant skillnad mellan de två grupperna kunde påvisas. Medelhastigheten för tacklingarna som resulterade i hjärnskakning var 6.55 m/s för den attackerande spelaren och 4.59 m/s för den skadade spelaren. Prototypen jämfördes också med hastigheter som tagits fram med SkillSpector i ett tidigare kandidatexamensarbete. Det var en signifikant skillnad mellan de hastigheter som togs fram med prototypen och de som tog fram med SkillSpector. En validering av SkillSpector gjordes också, som visade att medelfelet var 37.4%.
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Wong, Tzu Yen. "Image transition techniques using projective geometry." University of Western Australia. School of Computer Science and Software Engineering, 2009. http://theses.library.uwa.edu.au/adt-WU2009.0149.
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[Truncated abstract] Image transition effects are commonly used on television and human computer interfaces. The transition between images creates a perception of continuity which has aesthetic value in special effects and practical value in visualisation. The work in this thesis demonstrates that better image transition effects are obtained by incorporating properties of projective geometry into image transition algorithms. Current state-of-the-art techniques can be classified into two main categories namely shape interpolation and warp generation. Many shape interpolation algorithms aim to preserve rigidity but none preserve it with perspective effects. Most warp generation techniques focus on smoothness and lack the rigidity of perspective mapping. The affine transformation, a commonly used mapping between triangular patches, is rigid but not able to model perspective effects. Image transition techniques from the view interpolation community are effective in creating transitions with the correct perspective effect, however, those techniques usually require more feature points and algorithms of higher complexity. The motivation of this thesis is to enable different views of a planar surface to be interpolated with an appropriate perspective effect. The projective geometric relationship which produces the perspective effect can be specified by two quadrilaterals. This problem is equivalent to finding a perspectively appropriate interpolation for projective transformation matrices. I present two algorithms that enable smooth perspective transition between planar surfaces. The algorithms only require four point correspondences on two input images. ...The second algorithm generates transitions between shapes that lie on the same plane which exhibits a strong perspective effect. It recovers the perspective transformation which produces the perspective effect and constrains the transition so that the in-between shapes also lie on the same plane. For general image pairs with multiple quadrilateral patches, I present a novel algorithm that is transitionally symmetrical and exhibits good rigidity. The use of quadrilaterals, rather than triangles, allows an image to be represented by a small number of primitives. This algorithm uses a closed form force equilibrium scheme to correct the misalignment of the multiple transitional quadrilaterals. I also present an application for my quadrilateral interpolation algorithm in Seitz and Dyer's view morphing technique. This application automates and improves the calculation of the reprojection homography in the postwarping stage of their technique. Finally I unify different image transition research areas into a common framework, this enables analysis and comparison of the techniques and the quality of their results. I highlight that quantitative measures can greatly facilitate the comparisons among different techniques and present a quantitative measure based on epipolar geometry. This novel quantitative measure enables the quality of transitions between images of a scene from different viewpoints to be quantified by its estimated camera path.
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White, Jacob Harley. "Real-Time Visual Multi-Target Tracking in Realistic Tracking Environments." BYU ScholarsArchive, 2019. https://scholarsarchive.byu.edu/etd/7486.
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This thesis focuses on visual multiple-target tracking (MTT) from a UAV. Typical state-of-the-art multiple-target trackers rely on an object detector as the primary detection source. However, object detectors usually require a GPU to process images in real-time, which may not be feasible to carry on-board a UAV. Additionally, they often do not produce consistent detections for small objects typical of UAV imagery.In our method, we instead detect motion to identify objects of interest in the scene. We detect motion at corners in the image using optical flow. We also track points long-term to continue tracking stopped objects. Since our motion detection algorithm generates multiple detections at each time-step, we use a hybrid probabilistic data association filter combined with a single iteration of expectation maximization to improve tracking accuracy.We also present a motion detection algorithm that accounts for parallax in non-planar UAV imagery. We use the essential matrix to distinguish between true object motion and apparent object motion due to parallax. Instead of calculating the essential matrix directly, which can be time-consuming, we design a new algorithm that optimizes the rotation and translation between frames. This new algorithm requires only 4 ms instead of 47 ms per frame of the video sequence.We demonstrate the performance of these algorithms on video data. These algorithms are shown to improve tracking accuracy, reliability, and speed. All these contributions are capable of running in real-time without a GPU.
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Erdem, Elif. "Constructing Panoramic Scenes From Aerial Videos." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12609083/index.pdf.
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In this thesis, we address the problem of panoramic scene construction in which a single image covering the entire visible area of the scene is constructed from an aerial image video.
In the literature, there are several algorithms developed for construction of panoramic scene of a video sequence. These algorithms can be categorized as feature based and featureless algorithms. In this thesis, we concentrate on the feature based algorithms and comparison of these algorithms is performed for aerial videos. The comparison is performed on video sequences captured by non-stationary cameras, whose optical axis does not have to be the same. In addition, the matching and tracking performances of the algorithms are separately analyzed, their advantages-disadvantages are presented and several modifications are proposed.
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Komosný, Petr. "Detekce odpovídajících si bodů ve dvou fotografiích." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2009. http://www.nusl.cz/ntk/nusl-236763.
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This thesis is interested in detection of corresponding points in images, which display the same object, eventually some of important elements and synchronizing these images. The aim of this thesis is to find, study and choose suitable algorithm for detecting interesting points in image. This algorithm will be apply at couple of images and in these images will find couples of corresponding points across these images. Functional output of this thesis will be application which will realize choosen interesting points detector, algorithm for finding correspondencies of regions and their synchronizing and joint them to one output image.
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Bauda, Marie-Anne. "Compréhension de scènes urbaines par combinaison d'information 2D/3D." Phd thesis, Toulouse, INPT, 2016. http://oatao.univ-toulouse.fr/16483/1/BAUDA_MarieAnne.pdf.
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Cette thèse traite du problème de segmentation sémantique d'une séquence d'images calibrées acquises dans un environnement urbain. Ce problème consiste, plus précisément, à partitionner chaque image en régions représentant les objets de la scène (façades, routes, etc.). Ainsi, à chaque région est associée une étiquette sémantique. Dans notre approche, l'étiquetage s'opère via des primitives visuelles de niveau intermédiaire appelés super-pixels, lesquels regroupent des pixels similaires au sens de différents critères proposés dans la littérature, qu'ils soient photométriques (s'appuyant sur les couleurs) ou géométriques (limitant la taille des super-pixels formés). Contrairement à l'état de l'art, où les travaux récents traitant le même problème s'appuient en entrée sur une sur-segmentation initiale sans la remettre en cause, notre idée est de proposer, dans un contexte multi-vues, une nouvelle approche de constructeur de superpixels s'appuyant sur une analyse tridimensionnelle de la scène et, en particulier, de ses structures planes. Pour construire de «meilleurs» superpixels, une mesure de planéité locale, qui quantifie à quel point la zone traitée de l'image correspond à une surface plane de la scène, est introduite. Cette mesure est évaluée à partir d'une rectification homographique entre deux images proches, induites par un plan candidat au support des points 3D associés à la zone traitée. Nous analysons l'apport de la mesure UQI (Universal Quality Image) et montrons qu'elle se compare favorablement aux autres métriques qui ont le potentiel de détecter des structures planes. On introduit ensuite un nouvel algorithme de construction de super-pixels, fondé sur l'algorithme SLIC (Simple Linear Iterative Clustering) dont le principe est de regrouper les plus proches voisins au sens d'une distance fusionnant similarités en couleur et en distance, et qui intègre cette mesure de planéité. Ainsi la sur-segmentation obtenue, couplée à la cohérence interimages provenant de la validation de la contrainte de planéité locale de la scène, permet d'attribuer une étiquette à chaque entité et d'obtenir ainsi une segmentation sémantique qui partitionne l'image en objets plans.
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Lao, Yizhen. "3D Vision Geometry for Rolling Shutter Cameras." Thesis, Université Clermont Auvergne (2017-2020), 2019. http://www.theses.fr/2019CLFAC009/document.
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De nombreuses caméras CMOS modernes sont équipées de capteurs Rolling Shutter (RS). Ces caméras à bas coût et basse consommation permettent d’atteindre de très hautes fréquences d’acquisition. Dans ce mode d’acquisition, les lignes de pixels sont exposées séquentiellement du haut vers le bas de l'image. Par conséquent, les images capturées alors que la caméra et/ou la scène est en mouvement présentent des distorsions qui rendent les algorithmes classiques au mieux moins précis, au pire inutilisables en raison de singularités ou de configurations dégénérées. Le but de cette thèse est de revisiter la géométrie de la vision 3D avec des caméras RS en proposant des solutions pour chaque sous-tâche du pipe-line de Structure-from-Motion (SfM).Le chapitre II présente une nouvelle méthode de correction du RS en utilisant les droites. Contrairement aux méthodes existantes, qui sont itératives et font l’hypothèse dite Manhattan World (MW), notre solution est linéaire et n’impose aucune contrainte sur l’orientation des droites 3D. De plus, la méthode est intégrée dans un processus de type RANSAC permettant de distinguer les courbes qui sont des projections de segments droits de celles qui correspondent à de vraies courbes 3D. La méthode de correction est ainsi plus robuste et entièrement automatisée.Le chapitre III revient sur l'ajustement faisceaux ou bundle adjustment (BA). Nous proposons un nouvel algorithme basé sur une erreur de projection dans laquelle l’index de ligne des points projetés varie pendant l’optimisation afin de garder une cohérence géométrique contrairement aux méthodes existantes qui considère un index fixe (celui mesurés dans l’image). Nous montrons que cela permet de lever la dégénérescence dans le cas où les directions de scan des images sont trop proches (cas très communs avec des caméras embraquées sur un véhicule par exemple). Dans le chapitre VI nous étendons le concept d'homographie aux cas d’images RS en démontrant que la relation point-à-point entre deux images d’un nuage de points coplanaires pouvait s’exprimer sous la forme de 3 à 7 matrices de taille 3X3 en fonction du modèle de mouvement utilisé. Nous proposons une méthode linéaire pour le calcul de ces matrices. Ces dernières sont ensuite utilisées pour résoudre deux problèmes classiques en vision par ordinateur à savoir le calcul du mouvement relatif et le « mosaïcing » dans le cas RS.Dans le chapitre V nous traitons le problème de calcul de pose et de reconstruction multi-vues en établissant une analogie avec les méthodes utilisées pour les surfaces déformables telles que SfT (Structure-from-Template) et NRSfM (Non Rigid Structure-from-Motion). Nous montrons qu’une image RS d’une scène rigide en mouvement peut être interprétée comme une image Global Shutter (GS) d’une surface virtuellement déformée (par l’effet RS). La solution proposée pour estimer la pose et la structure 3D de la scène est ainsi composée de deux étapes. D’abord les déformations virtuelles sont d’abord calculées grâce à SfT ou NRSfM en assumant un modèle GS classique (relaxation du modèle RS). Ensuite, ces déformations sont réinterprétées comme étant le résultat du mouvement durant l’acquisition (réintroduction du modèle RS). L’approche proposée présente ainsi de meilleures propriétés de convergence que les approches existantesMany modern CMOS cameras are equipped with Rolling Shutter (RS) sensors which are considered as low cost, low consumption and fast cameras. In this acquisition mode, the pixel rows are exposed sequentially from the top to the bottom of the image. Therefore, images captured by moving RS cameras produce distortions (e.g. wobble and skew) which make the classic algorithms at best less precise, at worst unusable due to singularities or degeneracies. The goal of this thesis is to propose a general framework for modelling and solving structure from motion (SfM) with RS cameras. Our approach consists in addressing each sub-task of the SfM pipe-line (namely image correction, absolute and relative pose estimation and bundle adjustment) and proposing improvements.The first part of this manuscript presents a novel RS correction method which uses line features. Unlike existing methods, which uses iterative solutions and make Manhattan World (MW) assumption, our method R4C computes linearly the camera instantaneous-motion using few image features. Besides, the method was integrated into a RANSAC-like framework which enables us to detect curves that correspond to actual 3D straight lines and reject outlier curves making image correction more robust and fully automated.The second part revisits Bundle Adjustment (BA) for RS images. It deals with a limitation of existing RS bundle adjustment methods in case of close read-out directions among RS views which is a common configuration in many real-life applications. In contrast, we propose a novel camera-based RS projection algorithm and incorporate it into RSBA to calculate reprojection errors. We found out that this new algorithm makes SfM survive the degenerate configuration mentioned above.The third part proposes a new RS Homography matrix based on point correspondences from an RS pair. Linear solvers for the computation of this matrix are also presented. Specifically, a practical solver with 13 point correspondences is proposed. In addition, we present two essential applications in computer vision that use RS homography: plane-based RS relative pose estimation and RS image stitching. The last part of this thesis studies absolute camera pose problem (PnP) and SfM which handle RS effects by drawing analogies with non-rigid vision, namely Shape-from-Template (SfT) and Non-rigid SfM (NRSfM) respectively. Unlike all existing methods which perform 3D-2D registration after augmenting the Global Shutter (GS) projection model with the velocity parameters under various kinematic models, we propose to use local differential constraints. The proposed methods outperform stat-of-the-art and handles configurations that are critical for existing methods
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Kuzdas, Oldřich. "Skládání snímků panoramatického pohledu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2008. http://www.nusl.cz/ntk/nusl-217435.
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This paper deals step by step with process of stitching images taken by perspective camera rotated by its optical center into the panoramic image. There are described keypoint searching algorhytms, possibilities of calculating homography matrix and methods of eliminating unwanted seams between source images in final panoramic image. A part of this paper is also standalone application in which are implemented some algorhytms described in the work.
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Botero, galeano Diego andres. "Development of algorithms and architectures for driving assistance in adverse weather conditions using FPGAs." Thesis, Toulouse, INSA, 2012. http://www.theses.fr/2012ISAT0062/document.
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En raison de l'augmentation du volume et de la complexité des systèmes de transport, de nouveaux systèmes avancés d'assistance à la conduite (ADAS) sont étudiés dans de nombreuses entreprises, laboratoires et universités. Ces systèmes comprennent des algorithmes avec des techniques qui ont été étudiés au cours des dernières décennies, comme la localisation et cartographie simultanées (SLAM), détection d'obstacles, la vision stéréoscopique, etc. Grâce aux progrès de l'électronique, de la robotique et de plusieurs autres domaines, de nouveaux systèmes embarqués sont développés pour garantir la sécurité des utilisateurs de ces systèmes critiques. Pour la plupart de ces systèmes, une faible consommation d'énergie ainsi qu'une taille réduite sont nécessaires. Cela crée la contrainte d'exécuter les algorithmes sur les systèmes embarqués avec des ressources limitées. Dans la plupart des algorithmes, en particulier pour la vision par ordinateur, une grande quantité de données doivent être traitées à des fréquences élevées, ce qui exige des ressources informatiques importantes. Un FPGA satisfait cette exigence, son architecture parallèle combinée à sa faible consommation d'énergie et la souplesse pour les programmer permet de développer et d'exécuter des algorithmes plus efficacement que sur d'autres plateformes de traitement. Les composants virtuels développés dans cette thèse ont été utilisés dans trois différents projets: PICASSO (vision stéréoscopique), COMMROB (détection d'obstacles à partir d'une système multicaméra) et SART (Système d'Aide au Roulage tous Temps)Due to the increase of traffic volume and complexity of new transport systems, new Advanced Driver Assistance Systems (ADAS) are a subject of research of many companies, laboratories and universities. These systems include algorithms with techniques that have been studied during the last decades like Simultaneous Lo- calization and Mapping (SLAM), obstacle detection, stereo vision, etc. Thanks to the advances in electronics, robotics and other domains, new embedded systems are being developed to guarantee the safety of the users of these critical systems. For most of these systems a low power consumption as well as reduced size is required. It creates the constraint of execute the algorithms in embedded devices with limited resources. In most of algorithms, moreover for computer vision ones, a big amount of data must be processed at high frequencies, this amount of data demands strong computing resources. FPGAs satisfy this requirement; its parallel architecture combined with its low power consumption and exibility allows developing and executing some algorithms more efficiently than any other processing platforms. In this thesis different embedded computer vision architectures intended to be used in ADAS using FPGAs are presented such as: We present the implementation of a distortion correction architecture operating at 100 Hz in two cameras simultaneously. The correction module allows also to rectify two images for implementation of stereo vision. Obstacle detection algorithms based on Inverse Perspective Mapping (IPM) and classiffication based on Color/Texture attributes are presented. The IPM transform is based in the perspective effect of a scene perceived from two different points of view. Moreover results of the detection algorithms from color/texture attributes applied on a multi-cameras system, are fused in an occupancy grid. An accelerator to apply homographies on images, is presented; this accelerator can be used for different applications like the generation of Bird's eye view or Side view. Multispectral vision is studied using both infrared images and color ones. Syn- thetic images are generated from information acquired from visible and infrared sources to provide a visual aid to the driver. Image enhancement specific for infrared images is also implemented and evaluated, based on the Contrast Lim- ited Adaptive Histogram Equalization (CLAHE). An embedded SLAM algorithm is presented with different hardware acceler- ators (point detection, landmark tracking, active search, correlation, matrix operations). All the algorithms were simulated, implemented and verified using as target FPGAs. The validation was done using development kits. A custom board integrating all the presented algorithms is presented. Virtual components developed in this thesis were used in three different projects: PICASSO (stereo vision), COMMROB (obstacle detection from a multi-cameras system) and SART (multispectral vision)
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Ballard, Brett S. "Feature Based Image Mosaicing using Regions of Interest for Wide Area Surveillance Camera Arrays with Known Camera Ordering." University of Dayton / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1304090273.
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Tippetts, Beau J. "Real-Time Implementation of Vision Algorithm for Control, Stabilization, and Target Tracking for a Hovering Micro-UAV." BYU ScholarsArchive, 2008. https://scholarsarchive.byu.edu/etd/1418.
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A lightweight, powerful, yet efficient quad-rotor platform was designed and constructed to obtain experimental results of completely autonomous control of a hovering micro-UAV using a complete on-board vision system. The on-board vision and control system is composed of a Helios FPGA board, an Autonomous Vehicle Toolkit daughterboard, and a Kestrel Autopilot. The resulting platform is referred to as the Helio-copter. An efficient algorithm to detect, correlate, and track features in a scene and estimate attitude information was implemented with a combination of hardware and software on the FPGA, and real-time performance was obtained. The algorithms implemented include a Harris feature detector, template matching feature correlator, RANSAC similarity-constrained homography, color segmentation, radial distortion correction, and an extended Kalman filter with a standard-deviation outlier rejection technique (SORT). This implementation was designed specifically for use as an on-board vision solution in determining movement of small unmanned air vehicles that have size, weight, and power limitations. Experimental results show the Helio-copter capable of maintaining level, stable flight within a 6 foot by 6 foot area for over 40 seconds without human intervention.
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Dřevo, Aleš. "Rychlá re-kalibrace PTZ kamery pro analýzu dopravy." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2016. http://www.nusl.cz/ntk/nusl-255353.
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This thesis deals with problematics of PTZ-camera re-calibration during movement. The objective of this work is to keep the camera in calibration mode from default status when the known positions of Vanishing Points are in the image. With their use during movement, which is changing with motion of the camera, their positions are kept with help of two implemented methods. The first method is based on the principle of homography, the second on the principle of cross ratio. The results show that both of these methods work especially for keeping the positions of First Vanishing Points. In the case of the Second Vanishing Points there appear various problems and the results are often quite inaccurate.
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Arriaza, Barriga Romina Carolina. "Cycle-GAN for removing structured foreground objects in images." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-287536.
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The TRACAB Image Tracking System is used by ChyronHego for the tracking of ball and players on football fields. It requires the calibration of the cameras around the arena which is disrupted by fences and other mesh structures that are positioned between the camera and the field as a safety measure for the public. The purpose of this work was the implementation of a cycle consistent Generative Adversarial Network (cycle-GAN) for removing the fence from the image using unpaired data. Cycle-GANs are part of the state-of-the-art of image-to-image translation and can solve this kind of problem without the need of paired images. This makes it an exciting and powerful method and, according to the latest investigations in the current work, it has never been used for this kind of application before. The model was able to strongly attenuate, and in some cases completely remove, the net structure from images. To quantify the impact of the net removal a homography matching was performed. Then, it was compared with the homography associated to the baseline of blurring the image with a gaussian filter and the original image without the use of any filter. The results showed that the identification of key-points was harder on synthetic images than on the original image with or without small Gaussian filters, but it showed a better performance against images blurred with filters with a standard deviation of 3 pixels or more. Despite the performance not being better than the baseline in all the cases it always added new key-points, and sometimes, it was able to find correct homographies where the baseline could not. Therefore, the cycle-GAN model proved to complement the baseline.TRACAB Image Tracking System används av ChyronHego för spårning av bollen och spelaren påfotbollsplaner. Detta kräver kalibrering av kamerorna runt arenan som störs av staket och andra nätstrukturer som är placerade mellan kameran och fältet som en säkerhetsåtgärd för publiken. Detta examensabrete fokuserar påimplementeringen av en cycle-GAN för borttagning av nätet från bilden med hjälp av oparade data. Cycle-GAN är en bild-till-bild-översättning state-of-the-art teknik och det kan lösa denna typ av problem utan parade bilder. Detta gör det till en spännande och kraftfull metod och enligt den senaste forskningen har det aldrig använts för denna typ av tillämpning förut. Modellen kunde kraftigt dämpa och i vissa fall helt ta bort nätstrukturen från bilder. För att kvantifiera effekterna av avlägsnandet av nätet utfördes en homografimatchning. Därefter jämfördes det med homografin associerad med baslinjen där bilden görs suddig med ett gaussiskt filter och originalbilden utan användning av något filter. Resultaten visade att identifieringen av nyckelpunkter var svårare påsyntetiska bilder än påoriginalbilder med eller utan småGauss-filter, men det visade bättre prestanda än bilder som var suddigt med filter med en standardavvikelse på 3 pixlar eller mer. Trots att prestandan inte var bättre än baslinjen i alla fall lade versionen utan nätet alltid till nya nyckelpunkter, och ibland kunde den hitta korrekta homografier där baslinjen misslyckades. Därför, cycle-GAN-modellen kompletterar baslinjen.
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Salva, Karol T. "A Hybrid Approach to Aerial Video Image Registration." Wright State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=wright1483524722687971.
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Mousse, Ange Mikaël. "Reconnaissance d'activités humaines à partir de séquences multi-caméras : application à la détection de chute de personne." Thesis, Littoral, 2016. http://www.theses.fr/2016DUNK0453/document.
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La vision artificielle est un domaine de recherche en pleine évolution. Les nouvelles stratégies permettent d'avoir des réseaux de caméras intelligentes. Cela induit le développement de beaucoup d'applications de surveillance automatique via les caméras. Les travaux développés dans cette thèse concernent la mise en place d'un système de vidéosurveillance intelligente pour la détection de chutes en temps réel. La première partie de nos travaux consiste à pouvoir estimer de façon robuste la surface d'une personne à partir de deux (02) caméras ayant des vues complémentaires. Cette estimation est issue de la détection de chaque caméra. Dans l'optique d'avoir une détection robuste, nous avons fait recours à deux approches. La première approche consiste à combiner un algorithme de détection de mouvements basé sur la modélisation de l'arrière plan avec un algorithme de détection de contours. Une approche de fusion a été proposée pour rendre beaucoup plus efficiente le résultat de la détection. La seconde approche est basée sur les régions homogènes de l'image. Une première ségmentation est effectuée dans le but de déterminer les régions homogènes de l'image. Et pour finir, nous faisons la modélisation de l'arrière plan en se basant sur les régions. Une fois les pixels de premier plan obtenu, nous faisons une approximation par un polygone dans le but de réduire le nombre d'informations à manipuler. Pour l'estimation de cette surface nous avons proposé une stratégie de fusion dans le but d'agréger les détections des caméras. Cette stratégie conduit à déterminer l'intersection de la projection des divers polygones dans le plan de masse. La projection est basée sur les principes de l'homographie planaire. Une fois l'estimation obtenue, nous avons proposé une stratégie pour détecter les chutes de personnes. Notre approche permet aussi d'avoir une information précise sur les différentes postures de l'individu. Les divers algorithmes proposés ont été implémentés et testés sur des banques de données publiques dans le but de juger l'efficacité des approches proposées par rapport aux approches existantes dans l'état de l'art. Les résultats obtenus et qui ont été détaillés dans le présent manuscrit montrent l'apport de nos algorithmesArtificial vision is an involving field of research. The new strategies make it possible to have some autonomous networks of cameras. This leads to the development of many automatic surveillance applications using the cameras. The work developed in this thesis concerns the setting up of an intelligent video surveillance system for real-time people fall detection. The first part of our work consists of a robust estimation of the surface area of a person from two (02) cameras with complementary views. This estimation is based on the detection of each camera. In order to have a robust detection, we propose two approaches. The first approach consists in combining a motion detection algorithm based on the background modeling with an edge detection algorithm. A fusion approach has been proposed to make much more efficient the results of the detection. The second approach is based on the homogeneous regions of the image. A first segmentation is performed to find homogeneous regions of the image. And finally we model the background using obtained regions
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Riou, Cécile. "Architectures et apports de systèmes de vision light-field pour la vision par ordinateur." Thesis, Mulhouse, 2017. http://www.theses.fr/2017MULH0498/document.
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Cette thèse traite des caméras light-field en tant que caméra ayant des capacités 3D. Les images brutes, acquises avec ces systèmes, sont généralement inexploitables directement. L’obstacle majeur concernant l'utilisation de ces caméras réside dans la complexité du traitement des images acquises. Cette thèse vise à dépasser ces limitations en s'intéressant aux dispositifs multi-vues et multi-caméras. De plus, comme l'un des domaines d'application envisagé est la vision industrielle, les images sont acquises en lumière naturelle afin de conserver la possibilité d'effectuer des traitements conventionnels par vision sur les images. Le travail de thèse repose sur trois axes : l'étude et la conception optique de systèmes light-field multi-caméras et multi-vues, le calibrage de ces dispositifs et le développement d’algorithmes et enfin leur mise en application pour montrer les intérêts de ces caméras dans divers domainesThis thesis deals with light-field cameras as cameras having 3D capacities. The raw images. acquired with these systems, are generally unusable directly. The main obstacle about their use lies in the complex processing of the recorded images. This thesis aims to overcome these limitations by focusing on multi-views and multi-camera devices. Morcover, as one of the application domains is the industrial vision, the images are acquired in natural lightning in order to conserve the possibility to make conventional treatments by vision on the images. The work is based on three axis: the study and'the optical desien of light-field systems, the calibration of these devices and the development of algorithms to show the intercsts of these cameras in various fields
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Panahandeh, Ghazaleh, Nasser Mohammadiha, and Magnus Jansson. "Ground Plane Feature Detection in Mobile Vision-Aided Inertial Navigation." KTH, Signalbehandling, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-99448.
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In this paper, a method for determining ground plane features in a sequence of images captured by a mobile camera is presented. The hardware of the mobile system consists of a monocular camera that is mounted on an inertial measurement unit (IMU). An image processing procedure is proposed, first to extract image features and match them across consecutive image frames, and second to detect the ground plane features using a two-step algorithm. In the first step, the planar homography of the ground plane is constructed using an IMU-camera motion estimation approach. The obtained homography constraints are used to detect the most likely ground features in the sequence of images. To reject the remaining outliers, as the second step, a new plane normal vector computation approach is proposed. To obtain the normal vector of the ground plane, only three pairs of corresponding features are used for a general camera transformation. The normal-based computation approach generalizes the existing methods that are developed for specific camera transformations. Experimental results on real data validate the reliability of the proposed method.QC 20121107
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Nguyen, Lam Hung. "Contrôle non linéaire et guidage visuel de véhicules sous-marins." Thesis, Université Côte d'Azur (ComUE), 2019. http://theses.unice.fr/2019AZUR4095.
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Les récents progrès technologiques ont suscité un intérêt croissant pour les applications robotiques sous-marines. Historiquement, les contraintes liées à la charge utile ont fortement limité le développement des véhicules sous-marins à modèle réduit. Ils sont petits, leur dynamique est très non linéaire, soumis à des effets hydrodynamiques complexes et imprécis et à des perturbations proportionnables aux actions de contrôle. Par conséquent, ils constituent un terrain d'essai idéal pour les techniques de contrôle non-linéaire sophistiquées. Les techniques de contrôle classiques appliquées à ces véhicules semblent inadéquates pour faire face à leur dynamique hautement non-linéaire, aux incertitudes des modèles et aux perturbations externes. Une autre question clé qui se pose est la difficulté de la navigation dans des environnements encombrés et à proximité d'obstacles sans positionnement précis par rapport à l'environnement et sans mesure de vitesse. Dans la présente thèse, deux sujets de recherche ont été considérés: 1) Deux nouveaux schémas de contrôle par asservissement visuel dynamique (sans mesure de la vitesse linéaire) pour les véhicules sous-marins complètement actionnés ont été proposés. Ces deux contrôleurs ont été développés pour deux configurations différentes de la caméra : pointant vers le bas et vers l'avant. La principale contribution ici est de s’en passer du coûteux capteur de vitesse (DVL) utilisé pour mesurer la vitesse linéaire. Les performances des deux algorithmes de contrôle ont été validées par des simulations et via des essais pratiques dans un environnement très difficile. La plateforme expérimentale ainsi que le logiciel de développement a été conçue sur la période la thèse. 2) Nous avons proposé un nouvel algorithme de poursuite de trajectoire pour une classe de véhicules sous-déclenchés ayant une forme axisymétrique allongée. La méthode proposée utilise un nouveau modèle dynamique non linéaire du véhicule et exploite la symétrie du véhicule pour la synthèse de la conception des commandes. La performance de la loi de contrôle élaborée et sa robustesse ont été validées via des simulations en utilisant un modèle réaliste d'un véhicule sous-marinRecent advances in technology have led to a growing interest in underwater robotic applications.Historically, payload constraints have severely limited the development of scale-model underwatervehicles. They are small; their dynamics are highly nonlinear, subjected to complex and imprecisehydrodynamic effects and to disturbances commensurable with the control actions. Consequently, theyprovide an ideal testing ground for sophisticated nonlinear control techniques. Classical controltechniques applied to these vehicles seem to be inadequate in dealing with their highly nonlineardynamics, model uncertainties and external disturbances. Another key arising issue is the difficulty ofnavigation in cluttered environments and close to obstacles without precise positioning with respect tothe environment and without velocity measurements.In the present thesis, two research topics have been considered. Firstly, two novel dynamic visualservoing controllers exploiting the so-called homography matrix for fully-actuated vehicles (withoutmeasuring the linear velocity) have been proposed. These two approaches are derived for two differentcamera configurations: downward-looking and forward-looking. The key contribution here is thenon-requirement of costly Doppler Velocity Log (DVL) velocity sensor. The control performance hasbeen validated over simulations and via practical trials in a real challenging environment. Theexperimental platform as well as the software was built over the period of the thesis. Secondly, a noveltrajectory tracking algorithm for a class of underactuated vehicles with axisymmetric slender body hasbeen developed. The proposed approach makes use of a new nonlinear dynamic model of the vehicle,and exploits the symmetry of the vehicle in control design. The control performance and its robustnesshave been validated via simulations using a realistic model of an underwater vehicle
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Gerhardt, Damon Dyck. "Feature-based Mini Unmanned Air Vehicle Video Euclidean Stabilization with Local Mosaics." BYU ScholarsArchive, 2007. https://scholarsarchive.byu.edu/etd/1056.
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Video acquired using a camera mounted on a mini Unmanned Air Vehicle (mUAV) may be very helpful in Wilderness Search and Rescue and many other applications but is commonly plagued with limited spatial and temporal field of views, distractive jittery motions, disorienting rotations, and noisy and distorted images. These problems collectively make it very difficult for human viewers to identify objects of interest as well as infer correct orientations throughout the video. In order to expand the temporal and spatial field of view, stabilize, and better orient users of noisy and distorted mUAV video, a method is proposed of estimating in software and in real time the relative motions of each frame to the next by tracking a small subset of features within each frame to the next. Using these relative motions, a local Euclidean mosaic of the video can be created and a curve can be fit to the video's accumulative motion path to stabilize the presentations of both the video and the local Euclidean mosaic. The increase in users' abilities to perform common search-and-rescue tasks of identifying objects of interest throughout the stabilized and locally mosaiced mUAV video is then evaluated. Finally, a discussion of remaining limitations is presented along with some possibilities for future work.
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Župka, Jiří. "Orientace kamery v reálném čase." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2010. http://www.nusl.cz/ntk/nusl-237112.
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This work deals with the orientation of the camera in real-time with a single camera. Offline methods are described and used as a reference for comparison of a real-time metods. Metods work in real-time Monocular SLAM and PTAM methods are there described and compared. Further, paper shows hints of advanced methods whereas future work is possible.
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Skowronski, Robin. "Perception visuelle pour les drones légers." Thesis, Bordeaux 1, 2011. http://www.theses.fr/2011BOR14345/document.
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Dans cette thèse, en collaboration avec l'entreprise AéroDRONES, le Laboratoire Bordelais de Recherche en Informatique et l'INRIA, nous abordons le problème de la perception de l'environnement à partir d'une caméra embarquée sur un drone léger. Nous avons conçu, développé et validé de nouvelles méthodes de traitement qui optimisent l'exploitation des données produites par des systèmes de prise de vue aéroportés bas coût. D'une part, nous présentons une méthode d'autocalibrage de la caméra et de la tourelle d'orientation, sans condition spécifique sur l'environnement observé. Ensuite nous proposons un nouvel algorithme pour extraire la rotation de la caméra calibrée entre deux images (gyroscope visuel) et l'appliquons à la stabilisation vidéo en temps réel. D'autre part, nous proposons une méthode de géoréférencement des images par fusion avec un fond cartographique existant. Cette méthode permet d'enrichir des bases de données de photos aériennes, en gérant les cas de non-planéité du terrainThe last decade has seen the emergence of many Unmanned Aerial Vehicles (UAV) which are becoming increasingly cheap and miniaturized. A mounted video-camera is standard equipment and can be found on any such UAVs. In this context, we present robust techniques to enhance autonomy levels of airborne vision systems based on mini-UAV technologies. First, we present a camera autocalibration method based on central projection based image \dimension{2}-invariants analysis and we compare it to classical Dual Image of the Absolute Conic (DIAC) technique. We present also a method to detect and calibrate turret's effectors hierarchy. Then, we propose a new algorithm to extract a calibrated camera self-rotation (visual gyroscope) and we apply it to propose a real-time video stabilizer with full perspective correction