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Dissertations / Theses on the topic 'Histogram of Oriented Gradients (HOG)'
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Lienemann, Matthew A. "Automated Multi-Modal Search and Rescue using Boosted Histogram of Oriented Gradients." DigitalCommons@CalPoly, 2015. https://digitalcommons.calpoly.edu/theses/1507.
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Unmanned Aerial Vehicles (UAVs) provides a platform for many automated tasks and with an ever increasing advances in computing, these tasks can be more complex. The use of UAVs is expanded in this thesis with the goal of Search and Rescue (SAR), where a UAV can assist fast responders to search for a lost person and relay possible search areas back to SAR teams. To identify a person from an aerial perspective, low-level Histogram of Oriented Gradients (HOG) feature descriptors are used over a segmented region, provided from thermal data, to increase classification speed. This thesis also introduces a dataset to support a Bird’s-Eye-View (BEV) perspective and tests the viability of low level HOG feature descriptors on this dataset. The low-level feature descriptors are known as Boosted Histogram of Oriented Gradients (BHOG) features, which discretizes gradients over varying sized cells and blocks that are trained with a Cascaded Gentle AdaBoost Classifier using our compiled BEV dataset. The classification is supported by multiple sensing modes with color and thermal videos to increase classification speed. The thermal video is segmented to indicate any Region of Interest (ROI) that are mapped to the color video where classification occurs. The ROI decreases classification time needed for the aerial platform by eliminating a per-frame sliding window. Testing reveals that with the use of only color data iv and a classifier trained for a profile of a person, there is an average recall of 78%, while the thermal detection results with an average recall of 76%. However, there is a speed up of 2 with a video of 240x320 resolution. The BEV testing reveals that higher resolutions are favored with a recall rate of 71% using BHOG features, and 92% using Haar-Features. In the lower resolution BEV testing, the recall rates are 42% and 55%, for BHOG and Haar-Features, respectively.
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Chrápek, David. "Učení a detekce objektů různých tříd v obraze." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2012. http://www.nusl.cz/ntk/nusl-236481.
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This paper is focused on object learning and recognizing in the image and in the image stream. More specifically on learning and recognizing humans or theirs parts in case they are partly occluded, with possible usage on robotic platforms. This task is based on features called Histogram of Oriented Gradients (HOG) which can work quite well with different poses the human can be in. The human is split into several parts and those parts are detected individually. Then a system of voting is introduced in which detected parts votes for the final positions of found people. For training the detector a linear SVM is used. Then the Kalman filter is used for stabilization of the detector in case of detecting from image stream.
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Olejár, Adam. "Měření výšky postavy v obraze." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-220426.
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The aim of this paper is a summary of the theory necessary for a modification, detection of person and the height calculation of the detected person in the image. These information were then used for implementation of the algoritm. The first half reveals teoretical problems and solutions. Shows the basic methods of image preprocessing and discusses the basic concepts of plane and projective geometry and transformations. Then describes the distortion, that brings into the picture imperfections of optical systems of cameras and the possibilities of removing them. Explains HOG algorithm and the actual method of calculating height of person detected in the image. The second half describes algoritm structure and statistical evaluation.
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Dočekal, Martin. "Porovnání klasifikačních metod." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2019. http://www.nusl.cz/ntk/nusl-403211.
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This thesis deals with a comparison of classification methods. At first, these classification methods based on machine learning are described, then a classifier comparison system is designed and implemented. This thesis also describes some classification tasks and datasets on which the designed system will be tested. The evaluation of classification tasks is done according to standard metrics. In this thesis is presented design and implementation of a classifier that is based on the principle of evolutionary algorithms.
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Hussain, Sibt Ul. "Apprentissage machine pour la détection des objets." Phd thesis, Université de Grenoble, 2011. http://tel.archives-ouvertes.fr/tel-00722632.
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Le but de cette thèse est de développer des méthodes pratiques plus performantes pour la détection d'instances de classes d'objets de la vie quotidienne dans les images. Nous présentons une famille de détecteurs qui incorporent trois types d'indices visuelles performantes - histogrammes de gradients orientés (Histograms of Oriented Gradients, HOG), motifs locaux binaires (Local Binary Patterns, LBP) et motifs locaux ternaires (Local Ternary Patterns, LTP) - dans des méthodes de discrimination efficaces de type machine à vecteur de support latent (Latent SVM), sous deux régimes de réduction de dimension - moindres carrées partielles (Partial Least Squares, PLS) et sélection de variables par élagage de poids SVM (SVM Weight Truncation). Sur plusieurs jeux de données importantes, notamment ceux du PASCAL VOC2006 et VOC2007, INRIA Person et ETH Zurich, nous démontrons que nos méthodes améliorent l'état de l'art du domaine. Nos contributions principales sont : Nous étudions l'indice visuelle LTP pour la détection d'objets. Nous démontrons que sa performance est globalement mieux que celle des indices bien établies HOG et LBP parce qu'elle permet d'encoder à la fois la texture locale de l'objet et sa forme globale, tout en étant résistante aux variations d'éclairage. Grâce à ces atouts, LTP fonctionne aussi bien pour les classes qui sont caractérisées principalement par leurs structures que pour celles qui sont caractérisées par leurs textures. En plus, nous démontrons que les indices HOG, LBP et LTP sont bien complémentaires, de sorte qu'un jeux d'indices étendu qui intègre tous les trois améliore encore la performance. Les jeux d'indices visuelles performantes étant de dimension assez élevée, nous proposons deux méthodes de réduction de dimension afin d'améliorer leur vitesse et réduire leur utilisation de mémoire. La première, basée sur la projection moindres carrés partielles, diminue significativement le temps de formation des détecteurs linéaires, sans réduction de précision ni perte de vitesse d'exécution. La seconde, fondée sur la sélection de variables par l'élagage des poids du SVM, nous permet de réduire le nombre d'indices actives par un ordre de grandeur avec une réduction minime, voire même une petite augmentation, de la précision du détecteur. Malgré sa simplicité, cette méthode de sélection de variables surpasse toutes les autres approches que nous avons mis à l'essai.
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Kuřátko, Jiří. "Počítání lidí ve videu." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2016. http://www.nusl.cz/ntk/nusl-255470.
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This master's thesis prepared the programme which is able to follow the trajectories of the movement of people and based on this to create various statistics. In practice it is an effective marketing tool which can be used for instance for customer flow analyses, optimal evaluation of opening hours, visitor traffic analyses and for a lot of other benefits. Histograms of oriented gradients, SVM classificator and optical flow monitoring were used to solve this problem. The method of multiple hypothesis tracking was selected for the association data. The system's quality was evaluated from the video footage of the street with the large concentration of pedestrians and from the school's camera system, where the movement in the corridor was monitored and the number of people counted.
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Dvořák, Michal. "Detekce a rozpoznání dopravního značení." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-221299.
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The goal of this thesis is the utilization of computer vision methods, in a way that will lead to detection and identification of traffic signs in an image. The final application is to analyze video feed from a video camcorder placed in a vehicle. With focus placed on effective utilization of computer resources in order to achieve real time identification of signs in a video stream.
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Vajhala, Rohith, Rohith Maddineni, and Preethi Raj Yeruva. "Weapon Detection In Surveillance Camera Images." Thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-13565.
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Now a days, Closed Circuit Television (CCTV) cameras are installedeverywhere in public places to monitor illegal activities like armedrobberies. Mostly CCTV footages are used as post evidence after theoccurrence of crime. In many cases a person might be monitoringthe scene from CCTV but the attention can easily drift on prolongedobservation. Eciency of CCTV surveillance can be improved by in-corporation of image processing and object detection algorithms intomonitoring process.The object detection algorithms, previously implemented in CCTVvideo analysis detect pedestrians, animals and vehicles. These algo-rithms can be extended further to detect a person holding weaponslike rearms or sharp objects like knives in public or restricted places.In this work the detection of weapon from CCTV frame is acquiredby using Histogram of Oriented Gradients (HOG) as feature vector andarticial neural networks performing back-propagation algorithm forclassication.As a weapon in the hands of a human is considered to be greaterthreat as compared to a weapon alone, in this work the detection ofhuman in an image prior to a weapon detection has been found advan-tageous. Weapon detection has been performed using three methods.In the rst method, the weapon in the image is detected directly with-out human detection. Second and third methods use HOG and back-ground subtraction methods for detection of human prior to detectionof a weapon. A knife and a gun are considered as weapons of inter-est in this work. The performance of the proposed detection methodswas analysed on test image dataset containing knives, guns and im-ages without weapon. The accuracy rate 84:6% has been achievedby a single-class classier for knife detection. A gun and a knife havebeen detected by the three-class classier with an accuracy rate 83:0%.
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Němec, Jiří. "Detekce pohybujících se objektů ve video sekvenci." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2012. http://www.nusl.cz/ntk/nusl-412865.
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This thesis deals with methods for the detection of people and tracking objects in video sequences. An application for detection and tracking of players in video recordings of sport activities, e.g. hockey or basketball matches, is proposed and implemented. The designed application uses the combination of histograms of oriented gradients and classification based on SVM (Support Vector Machines) for detecting players in the picture. Moreover, a particle filter is used for tracking detected players. The whole system was fully tested and the results are shown in the graphs and tables with verbal descriptions.
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Memarzadeh, Milad. "Automated 2D Detection and Localization of Construction Resources in Support of Automated Performance Assessment of Construction Operations." Thesis, Virginia Tech, 2012. http://hdl.handle.net/10919/76908.
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This study presents two computer vision based algorithms for automated 2D detection of construction workers and equipment from site video streams. The state-of-the-art research proposes semi-automated detection methods for tracking of construction workers and equipment. Considering the number of active equipment and workers on jobsites and their frequency of appearance in a camera's field of view, application of semi-automated techniques can be time-consuming. To address this limitation, two new algorithms based on Histograms of Oriented Gradients and Colors (HOG+C), 1) HOG+C sliding detection window technique, and 2) HOG+C deformable part-based model are proposed and their performance are compared to the state-of-the-art algorithm in computer vision community. Furthermore, a new comprehensive benchmark dataset containing over 8,000 annotated video frames including equipment and workers from different construction projects is introduced. This dataset contains a large range of pose, scale, background, illumination, and occlusion variation. The preliminary results with average performance accuracies of 100%, 92.02%, and 89.69% for workers, excavators, and dump trucks respectively, indicate the applicability of the proposed methods for automated activity analysis of workers and equipment from single video cameras. Unlike other state-of-the-art algorithms in automated resource tracking, these methods particularly detects idle resources and does not need manual or semi-automated initialization of the resource locations in 2D video frames.Master of Science
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Novák, Pavel. "Vyhledávání objektů v obraze na základě předlohy." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-220583.
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This Thesis is focused to Image Object Detection using Template. Main Benefit of this Work is a new Method for sympthoms extraction from Histogram of Oriented Gradients using set of Comparators. In this used Work Methods of Image comparing and Sympthoms extraction are described. Main Part is given to Histogram of Oriented Gradients Method. We came out from this Method. In this Work is used small training Data Set (100 pcs.) verified by X-Validation, followed by tests on real Sceneries. Achieved success Rate using X-Validation is 98%. for SVM Algorithm.
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Venkatrayappa, Darshan. "Image matching using rotating filters." Thesis, Montpellier, 2015. http://www.theses.fr/2015MONTS200/document.
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De nos jours les algorithmes de vision par ordinateur abondent dans les applications de vidéo-surveillance, de reconstruction 3D, de véhicules autonomes, d'imagerie médicale, etc… La détection et la mise en correspondance d'objets dans les images constitue une étape clé dans ces algorithmes.Les méthodes les plus communes pour la mise en correspondance d'objets ou d'images sont basées sur des descripteurs locaux, avec tout d'abord la détection de points d'intérêt, puis l'extraction de caractéristiques de voisinages des points d'intérêt, et enfin la construction des descripteurs d'image.Dans cette thèse, nous présentons des contributions au domaine de la mise en correspondance d'images par l'utilisation de demi filtres tournants. Nous suivons ici trois approches : la première présente un nouveau descripteur à faible débit et une stratégie de mise en correspondance intégrés à une plateforme vidéo. Deuxièmement, nous construisons un nouveau descripteur local en intégrant la réponse de demi filtres tournant dans un histogramme de gradient orienté (HOG) ; enfin nous proposons une nouvelle approche pour la construction d'un descripteur utilisant des statistiques du second ordre. Toutes ces trois approches apportent des résultats intéressants et prometteurs.Mots-clés : Demi filtres tournants, descripteur local d'image, mise en correspondance, histogramme de gradient orienté (HOG), Différence de gaussiennesNowadays computer vision algorithms can be found abundantly in applications relatedto video surveillance, 3D reconstruction, autonomous vehicles, medical imaging etc. Image/object matching and detection forms an integral step in many of these algorithms.The most common methods for Image/object matching and detection are based on localimage descriptors, where interest points in the image are initially detected, followed byextracting the image features from the neighbourhood of the interest point and finally,constructing the image descriptor. In this thesis, contributions to the field of the imagefeature matching using rotating half filters are presented. Here we follow three approaches:first, by presenting a new low bit-rate descriptor and a cascade matching strategy whichare integrated on a video platform. Secondly, we construct a new local image patch descriptorby embedding the response of rotating half filters in the Histogram of Orientedgradient (HoG) framework and finally by proposing a new approach for descriptor constructionby using second order image statistics. All the three approaches provides aninteresting and promising results by outperforming the state of art descriptors.Key-words: Rotating half filters, local image descriptor, image matching, Histogram of Orientated Gradients (HoG), Difference of Gaussian (DoG)
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Svoboda, Tomáš. "Detekce, lokalizace a rozpoznání dopravních značek." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-236958.
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This master's thesis deals with the localization, detection and recognition of traffic signs. The possibilities of selection of areas with possible traffic signs occurrence are analysed. The properties of different kinds of features used for traffic signs recognition are described next. It focuses on the features based on histogram of oriented gradients. Some possible classifiers are discussed, in the first place the cascade of support vector machines, which are used in resulting system. A description of the system implementation and data sets for 5 types of traffic signs is part of this thesis. Many experiments were accomplished with created system. The results of the experiments are very good. New datasets were acquired from approximately 9 hours of processed video sequences. There are about 13 500 images in these datasets.
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Klos, Dominik. "Počítání tlakových lahví v obraze." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2014. http://www.nusl.cz/ntk/nusl-236055.
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This thesis deals with an automatic counting of cylinders placed on the back of a truck using images taken by a camera mounted above the car. To achieve this goal, an SVM classifier based on HOG image descriptors has been trained to detect the cylinders. Further, a tracking method based on optical flow estimation has been designed to track the cylinders through image sequences. The result of the thesis is an application that counts bottles with precision 93,08 % placed on the truck and visualizes results of the detection.
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Deaney, Mogammat Waleed. "A Comparison of Machine Learning Techniques for Facial Expression Recognition." University of the Western Cape, 2018. http://hdl.handle.net/11394/6412.
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Magister Scientiae - MSc (Computer Science)A machine translation system that can convert South African Sign Language (SASL) video to audio or text and vice versa would be bene cial to people who use SASL to communicate. Five fundamental parameters are associated with sign language gestures, these are: hand location; hand orientation; hand shape; hand movement and facial expressions. The aim of this research is to recognise facial expressions and to compare both feature descriptors and machine learning techniques. This research used the Design Science Research (DSR) methodology. A DSR artefact was built which consisted of two phases. The rst phase compared local binary patterns (LBP), compound local binary patterns (CLBP) and histogram of oriented gradients (HOG) using support vector machines (SVM). The second phase compared the SVM to arti cial neural networks (ANN) and random forests (RF) using the most promising feature descriptor|HOG|from the rst phase. The performance was evaluated in terms of accuracy, robustness to classes, robustness to subjects and ability to generalise on both the Binghamton University 3D facial expression (BU-3DFE) and Cohn Kanade (CK) datasets. The evaluation rst phase showed HOG to be the best feature descriptor followed by CLBP and LBP. The second showed ANN to be the best choice of machine learning technique closely followed by the SVM and RF.
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Vídeňský, František. "Počítačová podpora rozpoznávání a klasifikace rodových erbů." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2017. http://www.nusl.cz/ntk/nusl-363773.
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This master thesis describes the design and development of the system for detection and recognition of whole coat of arms as well as each heraldic parts. In the thesis are presented methods of computer vision for segmentation and detection of an object and selected methods that are the most suitable. Most of the heraldic parts are segmented using a convolution neural networks and the rest using active contours. The Histogram of the gradient method was selected for coats of arms detection in an image. For training and functionality verification is used my own data set. The resulting system can serve as an auxiliary tool used in auxiliary sciences of history.
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Khan, Rizwan Ahmed. "Détection des émotions à partir de vidéos dans un environnement non contrôlé." Thesis, Lyon 1, 2013. http://www.theses.fr/2013LYO10227/document.
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Dans notre communication quotidienne avec les autres, nous avons autant de considération pour l’interlocuteur lui-même que pour l’information transmise. En permanence coexistent en effet deux modes de transmission : le verbal et le non-verbal. Sur ce dernier thème intervient principalement l’expression faciale avec laquelle l’interlocuteur peut révéler d’autres émotions et intentions. Habituellement, un processus de reconnaissance d’émotions faciales repose sur 3 étapes : le suivi du visage, l’extraction de caractéristiques puis la classification de l’expression faciale. Pour obtenir un processus robuste apte à fournir des résultats fiables et exploitables, il est primordial d’extraire des caractéristiques avec de forts pouvoirs discriminants (selon les zones du visage concernées). Les avancées récentes de l’état de l’art ont conduit aujourd’hui à diverses approches souvent bridées par des temps de traitement trop couteux compte-tenu de l’extraction de descripteurs sur le visage complet ou sur des heuristiques mathématiques et/ou géométriques.En fait, aucune réponse bio-inspirée n’exploite la perception humaine dans cette tâche qu’elle opère pourtant régulièrement. Au cours de ces travaux de thèse, la base de notre approche fut ainsi de singer le modèle visuel pour focaliser le calcul de nos descripteurs sur les seules régions du visage essentielles pour la reconnaissance d’émotions. Cette approche nous a permis de concevoir un processus plus naturel basé sur ces seules régions émergentes au regard de la perception humaine. Ce manuscrit présente les différentes méthodologies bio-inspirées mises en place pour aboutir à des résultats qui améliorent généralement l’état de l’art sur les bases de référence. Ensuite, compte-tenu du fait qu’elles se focalisent sur les seules parties émergentes du visage, elles améliorent les temps de calcul et la complexité des algorithmes mis en jeu conduisant à une utilisation possible pour des applications temps réelCommunication in any form i.e. verbal or non-verbal is vital to complete various daily routine tasks and plays a significant role inlife. Facial expression is the most effective form of non-verbal communication and it provides a clue about emotional state, mindset and intention. Generally automatic facial expression recognition framework consists of three step: face tracking, feature extraction and expression classification. In order to built robust facial expression recognition framework that is capable of producing reliable results, it is necessary to extract features (from the appropriate facial regions) that have strong discriminative abilities. Recently different methods for automatic facial expression recognition have been proposed, but invariably they all are computationally expensive and spend computational time on whole face image or divides the facial image based on some mathematical or geometrical heuristic for features extraction. None of them take inspiration from the human visual system in completing the same task. In this research thesis we took inspiration from the human visual system in order to find from where (facial region) to extract features. We argue that the task of expression analysis and recognition could be done in more conducive manner, if only some regions are selected for further processing (i.e.salient regions) as it happens in human visual system. In this research thesis we have proposed different frameworks for automatic recognition of expressions, all getting inspiration from the human vision. Every subsequently proposed addresses the shortcomings of the previously proposed framework. Our proposed frameworks in general, achieve results that exceeds state-of-the-artmethods for expression recognition. Secondly, they are computationally efficient and simple as they process only perceptually salient region(s) of face for feature extraction. By processing only perceptually salient region(s) of the face, reduction in feature vector dimensionality and reduction in computational time for feature extraction is achieved. Thus making them suitable for real-time applications
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Perez, Eder de Almeida. "Descritor de movimento baseado em tensor e histograma de gradientes." Universidade Federal de Juiz de Fora (UFJF), 2012. https://repositorio.ufjf.br/jspui/handle/ufjf/3549.
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CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
O reconhecimento de padrões de movimentos tem se tornado um campo de pesquisa muito atrativo nos últimos anos devido, entre outros fatores, à grande massificação de dados em vídeos e a tendência na criação de interfaces homem-máquina que utilizam expressões faciais e corporais. Esse campo pode ser considerado um dos requisitos chave para análise e entendimento de vídeos. Neste trabalho é proposto um descritor de movimentos baseado em tensores de 2a ordem e histogramas de gradientes (HOG - Histogram of Oriented Gradients). O cálculo do descritor é rápido, simples e eficaz. Além disso, nenhum aprendizado prévio é necessário sendo que a adição de novas classes de movimentos ou novos vídeos não necessita de mudanças ou que se recalculem os descritores já existentes. Cada quadro do vídeo é particionado e em cada partição calcula-se o histograma de gradientes no espaço e no tempo. A partir daí calcula-se o tensor do quadro e o descritor final é formado por uma série de tensores de cada quadro. O descritor criado é avaliado classificando-se as bases de vídeos KTH e Hollywood2, utilizadas na literatura atual, com um classificador Máquina Vetor Suporte (SVM). Os resultados obtidos na base KTH são próximos aos descritores do estado da arte que utilizam informação local do vídeo. Os resultados obtidos na base Hollywood2 não superam o estado da arte, mas são próximos o suficiente para concluirmos que o método proposto é eficaz. Apesar de a literatura apresentar descritores que possuem resultados superiores na classificação, suas abordagens são complexas e de alto custo computacional.
The motion pattern recognition has become a very attractive research field in recent years due to the large amount of video data and the creation of human-machine interfaces that use facial and body expressions. This field can be considered one of the key requirements for analysis and understanding in video. This thesis proposes a motion descriptor based on second order tensor and histograms of oriented gradients. The calculation of the descriptor is fast, simple and effective. Furthermore, no prior knowledge of data basis is required and the addition of new classes of motion and videos do not need to recalculate the existing descriptors. The frame of a video is divided into a grid and the histogram of oriented gradients is computed in each cell. After that, the frame tensor is computed and the final descriptor is built by a series of frame tensors. The descriptor is evaluated in both KTH and Hollywood2 data basis, used in the current literature, with a Support Vector Machine classifier (SVM). The results obtained on the basis KTH are very close to the descriptors of the state-of-the-art that use local information of the video. The results obtained on the basis Hollywood2 not outweigh the state-of-the-art but are close enough to conclude that the proposed method is effective. Although the literature presents descriptors that have superior results, their approaches are complex and with computational cost.
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Chavali, Gautam Krishna, Sai Kumar N. V. Bhavaraju, Tushal Adusumilli, and VenuGopal Puripanda. "Micro-Expression Extraction For Lie Detection Using Eulerian Video (Motion and Color) Magnication." Thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3467.
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Lie-detection has been an evergreen and evolving subject. Polygraph techniques have been the most popular and successful technique till date. The main drawback of the polygraph is that good results cannot be attained without maintaining a physical contact, of the subject under test. In general, this physical contact would induce extra consciousness in the subject. Also, any sort of arousal in the subject triggers false positives while performing the traditional polygraph based tests. With all these drawbacks in the polygraph, also, due to rapid developments in the fields of computer vision and artificial intelligence, with newer and faster algorithms, have compelled mankind to search and adapt to contemporary methods in lie-detection. Observing the facial expressions of emotions in a person without any physical contact and implementing these techniques using artificial intelligence is one such method. The concept of magnifying a micro expression and trying to decipher them is rather premature at this stage but would evolve in future. Magnification using EVM technique has been proposed recently and it is rather new to extract these micro expressions from magnified EVM based on HOG features. Till date, HOG features have been used in conjunction with SVM, and generally for person/pedestrian detection. A newer, simpler and contemporary method of applying EVM with HOG features and Back-propagation Neural Network jointly has been introduced and proposed to extract and decipher the micro-expressions on the face. Micro-expressions go unnoticed due to its involuntary nature, but EVM is used to magnify them and makes them noticeable. Emotions behind the micro-expressions are extracted and recognized using the HOG features \& Back-Propagation Neural Network. One of the important aspects that has to be dealt with human beings is a biased mind. Since, an investigator is also a human and, he too, has to deal with his own assumptions and emotions, a Neural Network is used to give the investigator an unbiased start in identifying the true emotions behind every micro-expression. On the whole, this proposed system is not a lie-detector, but helps in detecting the emotions of the subject under test. By further investigation, a lie can be detected.This thesis uses a magnification technique to magnify the subtle, faint and spontaneous facial muscle movements or more precisely, micro-expressions. This magnification would help a system in classifying them and estimating the emotion behind them. This technique additionally magnifies the color changes, which could be used to extract the pulse without a physical contact with the subject. The results are presented in a GUI.
Gautam: +46(0)739528573, +91-9701534064 Tushal: +46(0)723219833, +91-9000242241 Venu: +46(0)734780266, +91-9298653191 Sai: +91-9989410111
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WANG, CHIA-CHENG, and 王嘉誠. "Handwritten digits recognition using histogram of oriented gradient(HOG) features." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/2htjrt.
Full textAbstract:
碩士輔仁大學
資訊工程學系碩士班
106
Convolutional neural network has a variety of applications in image recognition, and this type of neural network is effective for training features provided by the images from training data. The MNIST handwritten dataset is often used in training convolutional neural networks. In this study, we will train a multi-layer fully connected convolutional neural network on data we collected by using histogram of oriented gradient(HOG) to extract gradient features of the MNIST handwritten dataset. With five HOG features extracted datasets, proposed method has achieved an accuracy of 99.07% on the test data, and an accuracy of 98.88% on the validation data. In order to evaluate the performance of the trained model, we randomly generate 101 images with random noise. Each image contains 8 to 10 digits with random size and angle. The generated digits have different fonts from the MNIST handwritten dataset, our recognition test was able to scan the correct number of digits, and the trained model correctly identified 86.14% of the digits.
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Βλαχοστάθης, Σωτήριος. "Ανίχνευση ανθρώπου και παρακολούθηση της κίνησής του." Thesis, 2014. http://hdl.handle.net/10889/8221.
Full textAbstract:
Η διάδοση της χρήσης των υπολογιστών σε όλο και περισσότερους τομείς της καθημερινής μας ζωής, καθώς και η τεχνολογική εξέλιξη στην επιστήμη των υπολογιστών είχε σαν φυσικό επακόλουθο τη δημιουργία αλγορίθμων που έχουν στόχο την ανίχνευση και την αναγνώριση ανθρώπων με ακρίβεια καθώς και την παρακολούθηση τους.
Τέτοιοι αλγόριθμοι εφαρμόζονται κυρίως σε συστήματα οπτικής επιτήρησης που είναι ζωτικής σημασίας σε διάφορους τομείς της καθημερινότητας.
Αντικείμενο της παρούσας διπλωματικής εργασίας είναι η υλοποίηση ενός συστήματος ανίχνευσης, με τη χρήση του αλγόριθμου Histogram of Oriented Gradient (HOG), ταξινόμησης με χρήση Supported Vector Machines και παρακολούθησης ανθρώπου σε ακολουθία εικόνων, με χρήση αλγορίθμων υπολογιστικής όρασης όπως είναι ο αλγόριθμος φιλτραρίσματος σωματιδίων (Particle Filtering).The widespread use of computers in more and more areas of our everyday life and the technological development in computer science as a natural consequence was the creation of algorithms that aim to detect and identify people accurately and monitor them. Such algorithms, are applied mainly in visual surveillance systems and is of vital importance in various areas of everyday life. The subject of this thesis is to implement a detection system using the algorithm Histogram of Oriented Gradient (HOG) as well, sort using Supported Vector Machines and the human tracking in image sequence, using computer vision algorithms such as Particle Filtering algorithm.
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Chen, Kuan-Yu, and 陳冠宇. "Hardware Implementation of Histogram of Oriented Gradients on Zynq." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/43948624554223648679.
Full textAbstract:
碩士輔仁大學
電機工程學系碩士班
104
Histogram of Oriented Gradients is a highly important research topic in image processing. One of the extensions of Histogram of Oriented Gradients, pedestrian detection algorithm, has been widely applied in areas that are closely related with people’s life, for example, visual surveillance and driver assistance. In the past, restrained by the complexity of its computation, Histogram of Oriented Gradients was forced to be only implemented on personal computer which caused disadvantages, such as power waste and limited application. We proposed to utilize FPGA to operate Histogram of Oriented Gradients on Zynq ZC702 development board. Through High Level Synthesis, we are able to use C-code to accelerate the design of IP core. In our solution, we have found through Pipeline of FPGA, the speed of computing Histogram of Gradients has increased 510 times compare to the speed of software architecture computation on the ZC702 development board in full HD image.
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Bing-Chang, Kuo, and 郭秉璋. "Histogram of Oriented Gradients based Arm Gesture Recognition Research." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/22769053839918102755.
Full textAbstract:
碩士國立臺灣師範大學
資訊工程研究所
100
In recently classroom environment, there are more and more teachers using electronic devices to help them easy to understand what students think and how students act. In all gestures, raising hand is the most popular way that students interacting with teachers. In this research, we provided a raising hand recognition system to help teacher to handle all students’ behavior. We use camera in complex background and monitor multiple people. To propose a system that can satisfy all environments and will not re-train after changing environments, we separate the system into two parts: people segmentation and gesture recognition. In people segmentation part, we use k-means clustering to extract skin color and then use motion to remove skin-liked background. In gesture recognition part, we use histogram of oriented gradient to get the gesture feature and then use SVM to classify. Finally in experimental part, we test 3 scenes to verify our method. When we use the same case to train and test, the correct rate is average 91%. Even we use different day for training/testing, the correct rate can also reach 80%.
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CHEN, TING-AN, and 陳亭安. "Real-time Intelligent Multi-object Recognition System Design Based on Generic Fourier Descriptor and Histogram of Oriented Gradients." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/y35236.
Full textAbstract:
碩士國立交通大學
電控工程研究所
108
In recent years, object image recognition has been a popular issue and lots of algorithms and applications are proposed. This thesis proposes a real-time multi-object recognition system based on generic Fourier descriptor and histogram of oriented gradients algorithms. The proposed system includes three parts, pre-processing, feature extraction and object recognition. First, during the period of pre-processing, the background of an input image is removed and only the objects to be recognized retain in the image. Second, generic Fourier descriptor is adopted to extract shape features of objects, and histogram of oriented gradients is used due to its invariance of geometric and photometric transformations for object orientations. Finally, the neural network classifier designed by the back-propagation algorithm is utilized to fulfill the proposed object recognition system. From the experimental results, the system could recognize objects in real-time with high accuracy rate, which verifies the effectiveness and efficiency of the proposed real-time detection system.
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Wei-KangFan and 范維康. "Multiple People Smile Intensity Estimation Using Multi-Region Histogram of Oriented Gradients with Discriminative Classification of Smiling Face Clues." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/44070641536023317279.
Full textAbstract:
碩士國立成功大學
電機工程學系碩博士班
100
With the advancement of technology, it is common for people to work with personal computers. However, people work under pressure with long hours and pile up stress in the nervous condition without awareness. There are many products and devices are developed to detect the health of body but less for the mental health. It is natural for people to convey their happiness with smiling faces. Therefore, based on the human natural, the thesis proposed a system which can remind people to sooth the nervous mental state by detecting and recording the appearance of smiling face to care the mental health of people. Smiling face detection can be categorized to the facial expression recognition (FER). There are several researches about FER in the field of image and video processing. According to the feature extraction manners, the FER system can be divided into geometric-based, appearance-based approaches and the hybrid-based approaches. All of the approaches have their own advantages and disadvantages. In order to detect the smiling face without disturbing the users, the system makes a tradeoff between the accuracy rate and computation power. The thesis proposed a new hybrid-based feature called multi-region histogram of oriented gradients (MRHOGs) which adopts the active shape model (ASM) for region extraction preprocessing, and shape characteristics for smiling face detection. The MRHOGs can represent both the orientation histogram and spatial information for the shapes of facial features which are also the major clues for humans to recognize the expressions. According to the characteristics of MRHOGs, the discriminative classification smiling face clues is designed for smiling face intensity estimation. The support vector machines (SVMs) are trained to detect the smiling face clues in the input image. By integrating the discriminative smiling face clues, the smiling face intensity can be estimated. The experiments were hold on JAFFE and FERET database and the worst case that smiles a little can also achieve the accuracy rate of 80%. There are higher accuracy rates for other clear smiling faces. Moreover, the method does not convolute the image with filter banks or need a large number of iteration to obtain the precise face model, which make the vector size smaller and computational power less to achieve a real-time system.
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Αντωνόπουλος, Γεώργιος. "Υλοποίηση σε FPGA του περιγραφέα HOG για ανίχνευση ανθρώπων σε εικόνες και βίντεο." Thesis, 2013. http://hdl.handle.net/10889/6504.
Full textAbstract:
Η παρούσα ειδική ερευνητική εργασία εκπονήθηκε στα πλαίσια του Διατμηματικού Προγράμματος Μεταπτυχιακών Σπουδών στην “Ηλεκτρονική και Επεξεργασία της Πληροφορίας”, στο Τμήμα Φυσικής του Πανεπιστημίου Πατρών. Αντικείμενο της παρούσας εργασίας είναι η “Υλοποίηση σε FPGA του περιγραφέα HOG για ανίχνευση ανθρώπων σε εικόνες και βίντεο”.
Το πρώτο κεφάλαιο αποτελεί μια εισαγωγή στις βασικότερες έννοιες που χρησιμοποιούνται στην παρούσα εργασία. Περιγράφεται επίσης η αναπτυξιακή πλακέτα που χρησιμοποιήθηκε καθώς και τα επί μέρους στοιχεία που τη συνθέτουν. Τέλος γίνεται μια συνοπτική αναφορά σε εργασίες με παρόμοιο αντικείμενο, οι οποίες με επηρέασαν στο σχεδιασμό και την υλοποίηση του συστήματός μου.
Στο δεύτερο κεφάλαιο αναλύεται ο περιγραφέας Ιστογραμμάτων Προσανατολισμού της Βάθμωσης ή όπως είναι ευρύτερα γνωστός Histograms of Oriented Gradient Descriptor. Παρουσιάζονται τα βήματα όπως περιγράφονται στην εργασία των Dalal&Triggs[4] και οι βέλτιστες τιμές των παραμέτρων του περιγραφέα.
Στο τρίτο κεφάλαιο ακολουθώντας τα βήματα του δευτέρου κεφαλαίου, παρουσιάζεται η διαδικασία υλοποίησης του περιγραφέα στο Matlab. Εκτός της υλοποίησης έγινε και μια προεργασία για τη μεταφορά του σε γλώσσα περιγραφής υλικού. Η προεργασία αυτή περιλαμβάνει απλοποιήσεις και τροποποιήσεις με σκοπό να μειωθεί το υπολογιστικό κόστος. Τέλος παρουσιάζονται τα αποτελέσματα δοκιμών της απόδοσης του περιγραφέα για τις διάφορες απλοποιήσεις.
Στο τέταρτο κεφάλαιο γίνεται μια μικρή αναφορά στους ταξινομητές. Περιγράφονται οι ταξινομητές που δοκιμάστηκαν στην παρούσα εργασία ως προς συγκεκριμένα χαρακτηριστικά τους καθώς και την υπολογιστική τους πολυπλοκότητα για την συγκεκριμένη εφαρμογή.
Το πέμπτο και τελευταίο κεφάλαιο περιλαμβάνει την περιγραφή της υλοποίησης σε VHDL. Αναλύονται τα επί μέρους κυκλώματα και όπου κρίθηκε αναγκαίο χρησιμοποιήθηκαν σχήματα ή πίνακες. Σε κάποιες περιπτώσεις δίνονται και οι κυματομορφές των κυκλωμάτων.This thesis took place within the frame work of the Interdeparmental Master’s Program in “Electronics and Information Processing”, at the Department of Physics of University of Patras. The objective of this work is the implementation in FPGA of the HOG descriptor for the detection of people, images and videos. The first chapter is an introduction about the basic concepts, which are used across the manuscript. (Additional descriptions concern the development board which was used as well as the individual parts that compose it.) In the end, there is a brief reference to past projects focusing on similar objectives, which influenced the design and the implementation of my system. The second chapter concerns the presentation and discussion of the Histograms of Oriented Gradient descriptor. The steps of the procedure and the best parameter values of the descriptor are presented in a similar way as they are described in the paper of Dalal and Triggs. In the third chapter, following the steps of the previous one, the focus shifts to the descriptor’s implementation procedure in Matlab. Besides the implementation, there is a preparation for the transference of the descriptor in a Hardware Description Language. This preparation includes simplifications and modifications aiming at the reduction of the computational cost. Finally, we see the tests’ results of the descriptor’s performance concerning the various simplifications. The fourth chapter is a partial reference to the classifiers. The description is about the classifiers that were used in the present work with respect to their features and their computational complexity of this particular application. The fifth and final chapter refers to the description of the implementation in VHDL. There is an analysis of the partial circuits and, when necessary, shapes and tables were used. In some cases, the waveforms of the circuits are being presented.
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Prabhu, Gayatri D. "Automated Detection and Counting of Pedestrians on an Urban Roadside." 2011. https://scholarworks.umass.edu/theses/708.
Full textAbstract:
This thesis implements an automated system that counts pedestrians with 85% accuracy. Two approaches have been considered and evaluated in terms of count accuracy, cost and ease of deployment. The first approach employs the Autoscope Solo Terra, a traffic camera which is widely used to monitor vehicular traffic. The Solo Terra supports an image processing-based detector that counts the number of objects crossing user-defined areas in the captured image. The count is updated based on the amount of movement across the selected regions. Therefore, a second approach has been considered that uses a histogram of oriented gradients (HoG), an advanced vision based algorithm proposed by Dalal et al. which distinguishes a pedestrian from a non-pedestrian based on an omega shape formed by the head and shoulders of a human being. The implemented detection software processes video frames that are streamed from a low-cost digital camera. The frames are divided into sub-regions which are scanned for an omega shape whenever movement is detected in those regions. It has been found that the HoG-based approach degrades in performance due to occlusion under dense pedestrian traffic conditions whereas the Solo Terra approach appears to be more robust. Undercounts and overcounts were encountered using the Solo Terra approach. To combat the disadvantages of both the approaches, they were integrated to form a single system where count is incremented predominantly using the Solo Terra. The HoG-based approach corrects the obtained count under certain conditions. A preliminary prototype of the integrated system has been verified.