Dissertations / Theses on the topic 'Epipolair geometry'

This thesis is dedicated photogrammetric image analysis that makes it possible from your photos with the help selected methods to determine the location and dimensions of objects recorded on them. There are explained the basics of photogrammetry and its current application. Chapters focused on digital imaging describing its characteristics, treatment options and key points findability for the scene calibration. For a comprehensive view are in this thesis introduced examples of existing software, its possibilities and use in practice.

Visual odometry is one of the prevalent techniques for the positioning of autonomous agents equipped with cameras. Several recent works in this field have in various ways attempted to exploit the capabilities of deep neural networks to improve the performance of visual odometry solutions. One of such approaches is using an end-to-end learning-based solution to infer the egomotion of the camera from a sequence of input images. The state of the art end-to-end solutions employ a common self-supervised training strategy that minimises a notion of photometric error formed by the view synthesis of the input images. As this error is a function of the predicted egomotion, its minimisation corresponds to the learning of egomotion estimation by the network. However, this also requires the depth information of the images, for which an additional depth estimation network is introduced in training. This implies that for end-to-end learning of camera egomotion, a set of parameters are required to be learned, which are not used in inference. In this work, we propose a novel learning strategy using epipolar geometry, which does not rely on depth estimations. Empirical evaluation of our method demonstrates its comparable performance to the baseline work that relies on explicit depth estimations for training.
Visuell odometri är en av de vanligast förekommande teknikerna för positionering av autonoma agenter utrustade med kameror. Flera senare arbeten inom detta område har på olika sätt försökt utnyttja kapaciteten hos djupa neurala nätverk för att förbättra prestandan hos lösningar baserade på visuell odometri. Ett av dessa tillvägagångssätt består i att använda en inlärningsbaserad lösning för att härleda kamerans rörelse utifrån en sekvens av bilder. Gemensamt för de flesta senare lösningar är en självövervakande träningsstrategi som minimerar det uppfattade fotometriska fel som uppskattas genom att syntetisera synvinkeln utifrån givna bildsekvenser. Eftersom detta fel är en funktion av den estimerade kamerarörelsen motsvarar minimering av felet att nätverket lär sig uppskatta kamerarörelsen. Denna inlärning kräver dock även information om djupet i bilderna, vilket fås genom att introducera ett nätverk specifikt för estimering av djup. Detta innebär att för uppskattning av kamerans rörelse krävs inlärning av ytterligare en uppsättning parametrar vilka inte används i den slutgiltiga uppskattningen. I detta arbete föreslår vi en ny inlärningsstrategi baserad på epipolär geometri, vilket inte beror på djupskattningar. Empirisk utvärdering av vår metod visar att dess resultat är jämförbara med tidigare metoder som använder explicita djupskattningar för träning.

A estimação de posição é o resultado direto da reconstrução de cenas, um dos ramos da visão computacional. É também uma informação importante para o controle de sistemas mecatrônicos, e em especial para os sistemas robóticos autônomos. Como uma aplicação de engenharia, o desempenho de tal sistema deve ser avaliado em termos de eficiência e eficácia, medidas traduzidas respectivamente pelo custo de processamento e pela quantificação do erro. A geometria epipolar é um campo da visão computacional que fornece formalismo matemático e técnicas de reconstrução de cenas a partir de uma par de imagens, através de pontos correspondentes entre elas. Através deste formalismo é possível determinar a incerteza dos métodos de estimação de posição, que são relativamente simples e podem atingir boa precisão. Dentre os sistemas robóticos autônomos destacam-se os ROVs - do inglês \"Remotely Operated Vehicles\" - ou veículos operados remotamente, muito utilizados em tarefas submarinas, e cuja necessidade crescente de autonomia motiva o desenvolvimento de um sensor de visão com características de baixo consumo de energia, flexibilidade e inteligência. Este sensor pode consistir de uma câmera CCD e algoritmos de reconstrução de cena baseados em geometria epipolar entre imagens. Este estudo visa fornecer um comparativo de resultados práticos da estimação de posição através da geometria epipolar entre imagens, como parte da implementação de um sensor de visão para robôs autônomos. Os conceitos teóricos abordados são: geometria projetiva, modelo de câmera, geometria epipolar, matriz fundamental, reconstrução projetiva, re-construção métrica, algoritmos de determinação da matriz fundamental, algoritmos de reconstrução métrica, incerteza da matriz fundamental e complexidade computacional. Os resultados práticos baseiam-se em simulações através de imagens geradas por computador e em montagens experimentais feitas em laboratório que simulam situações práticas. O processo de estimação de posição foi realizado através da implementação em MATLAB® 6.5 dos algoritmos apresentados na parte teórica, e os resultados comparados e analisados quanto ao erro e complexidade de execução. Dentre as principais conclusões é apresentado a melhor escolha para a implementação de sensor de visão de propósito geral - o Algoritmo de 8 Pontos Correspondentes Normalizado. São apresentadas também as condições de utilização de cada método e os cuidados necessários na interpretação dos resultados.
Position estimation is the direct result of scene reconstruction, one of computer vision\'s fields. It is also an important information for the control of mechanical systems - specially the autonomous robotic systems. As an engineering application, those systems\' performance must be evaluated in terms of efficiency and effectiveness, measured by processing costs and error quantification. The epipolar geometry is a field of computer vision that supply mathematical formalism and scene reconstruction techniques that are based on the correspondences between two images. Through this formalism it is possible to stipulate the uncertainty of the position estimation methods that are relatively simple and can give good accuracy. Among the autonomous robotic systems, the ROVs - Remotely Operated Vehicles - are of special interest, mostly employed in submarine activities, and whose crescent autonomy demand motivates the development of a vision sensor of low power consumption, flexibility and intelligence. This sensor may be constructed with a CCD camera and the scene reconstruction algorithms based on epipolar geometry. This work aims to build a comparison of practical results of position estimation through epipolar geometry, as part of a vision sensor implementation for autonomous robots. The theory presented in this work comprises of: projective geometry, camera model, epipolar geometry, fundamental matrix, projective reconstruction, metric reconstruction, fundamental matrix algorithms, metric reconstruction algorithms, fundamental matrix uncertainty, and computational complexity. The practical results are based on computer generated simulations and experimental assemblies that emulate practical issues. The position estimation was carried out by MATLAB® 6.5 implementations of the algorithms analyzed in the theoretical part, and the results are compared and analyzed in respect of the error and the execution complexity. The main conclusions are that the best algorithm choice for the implementation of a general purpose vision sensor is the Normalized 8 Point Algorithm, and the usage conditions of each method, besides the special considerations that must be observed at the interpretation of the results.

Sistemas de teleconferência e telepresença são ferramentas de comunicação cada vez mais comuns. Partindo da existência de um canal de comunicação de alta capacidade, busca-se permitir visualização tridimensional realista, sensível ao ponto de vista do usuário e que mantenha a estrutura física da cena sem conhecimento prévio de sua estrutura, por meio de câmeras estéreo. A partir de pares de imagens temporalmente coerentes são sintetizadas visões intermediárias da cena alvo, de modo que um usuário rastreado tenha a ilusão de estar vendo a cena real através de uma janela. O sistema implementado baseia-se em dispositivos que provejam melhor qualidade visual no componente de geração de imagens intermediárias e procura maximizar a facilidade de uso na parte de visualização, empregando dispositivos domésticos e dispensando procedimentos complexos de calibração.
Teleconference and telepresence systems are increasingly common. Based on the existence of a high capacity communication channel, it is aimed to provide user\'s point of view sensible realistic 3D visualization without physical distortion or any prior knowledge about the structure of the scene, using stereo cameras. Pairs of temporally coherent images are used to generate intermediary view of the target scene so that a tracked user will have the illusion of posing in front so the real scene. The implemented system is based on high visual quality components on the side of views generation and tries to maximize ease of use in the visualization part by using commodity components and being free so complex calibration procedures.

Aquesta tesi s'emmarca dins del projecte CICYT TAP 1999-0443-C05-01. L'objectiu d'aquest projecte és el disseny, implementació i avaluació de robots mòbils, amb un sistema de control distribuït, sistemes de sensorització i xarxa de comunicacions per realitzar tasques de vigilància. Els robots han de poder-se moure per un entorn reconeixent la posició i orientació dels diferents objectes que l'envolten. Aquesta informació ha de permetre al robot localitzar-se dins de l'entorn on es troba per poder-se moure evitant els possibles obstacles i dur a terme la tasca encomanada. El robot ha de generar un mapa dinàmic de l'entorn que serà utilitzat per localitzar la seva posició. L'objectiu principal d'aquest projecte és aconseguir que un robot explori i construeixi un mapa de l'entorn sense la necessitat de modificar el propi entorn.
Aquesta tesi està enfocada en l'estudi de la geometria dels sistemes de visió estereoscòpics formats per dues càmeres amb l'objectiu d'obtenir informació geomètrica 3D de l'entorn d'un vehicle. Aquest objectiu tracta de l'estudi del modelatge i la calibració de càmeres i en la comprensió de la geometria epipolar. Aquesta geometria està continguda en el que s'anomena emph{matriu fonamental}. Cal realitzar un estudi del càlcul de la matriu fonamental d'un sistema estereoscòpic amb la finalitat de reduir el problema de la correspondència entre dos plans imatge. Un altre objectiu és estudiar els mètodes d'estimació del moviment basats en la geometria epipolar diferencial per tal de percebre el moviment del robot i obtenir-ne la posició. Els estudis de la geometria que envolta els sistemes de visió estereoscòpics ens permeten presentar un sistema de visió per computador muntat en un robot mòbil que navega en un entorn desconegut. El sistema fa que el robot sigui capaç de generar un mapa dinàmic de l'entorn a mesura que es desplaça i determinar quin ha estat el moviment del robot per tal de emph{localitzar-se} dins del mapa.
La tesi presenta un estudi comparatiu dels mètodes de calibració de càmeres més utilitzats en les últimes dècades. Aquestes tècniques cobreixen un gran ventall dels mètodes de calibració clàssics. Aquest mètodes permeten estimar els paràmetres de la càmera a partir d'un conjunt de punts 3D i de les seves corresponents projeccions 2D en una imatge. Per tant, aquest estudi descriu un total de cinc tècniques de calibració diferents que inclouen la calibració implicita respecte l'explicita i calibració lineal respecte no lineal. Cal remarcar que s'ha fet un gran esforç en utilitzar la mateixa nomenclatura i s'ha estandaritzat la notació en totes les tècniques presentades. Aquesta és una de les dificultats principals a l'hora de poder comparar les tècniques de calibració ja què cada autor defineix diferents sistemes de coordenades i diferents conjunts de paràmetres. El lector és introduït a la calibració de càmeres amb la tècnica lineal i implícita proposada per Hall i amb la tècnica lineal i explicita proposada per Faugeras-Toscani. A continuació es passa a descriure el mètode a de Faugeras incloent el modelatge de la distorsió de les lents de forma radial. Seguidament es descriu el conegut mètode proposat per Tsai, i finalment es realitza una descripció detallada del mètode de calibració proposat per Weng. Tots els mètodes són comparats tant des del punt de vista de model de càmera utilitzat com de la precisió de la calibració. S'han implementat tots aquests mètodes i s'ha analitzat la precisió presentant resultats obtinguts tant utilitzant dades sintètiques com càmeres reals.
Calibrant cada una de les càmeres del sistema estereoscòpic es poden establir un conjunt de restriccions geomètri ques entre les dues imatges. Aquestes relacions són el que s'anomena geometria epipolar i estan contingudes en la matriu fonamental. Coneixent la geometria epipolar es pot: simplificar el problema de la correspondència reduint l'espai de cerca a llarg d'una línia epipolar; estimar el moviment d'una càmera quan aquesta està muntada sobre un robot mòbil per realitzar tasques de seguiment o de navegació; reconstruir una escena per aplicacions d'inspecció, propotipatge o generació de motlles. La matriu fonamental s'estima a partir d'un conjunt de punts en una imatges i les seves correspondències en una segona imatge. La tesi presenta un estat de l'art de les tècniques d'estimació de la matriu fonamental. Comença pels mètode lineals com el dels set punts o el mètode dels vuit punts, passa pels mètodes iteratius com el mètode basat en el gradient o el CFNS, fins arribar las mètodes robustos com el M-Estimators, el LMedS o el RANSAC. En aquest treball es descriuen fins a 15 mètodes amb 19 implementacions diferents. Aquestes tècniques són comparades tant des del punt de vista algorísmic com des del punt de vista de la precisió que obtenen. Es presenten el resultats obtinguts tant amb imatges reals com amb imatges sintètiques amb diferents nivells de soroll i amb diferent quantitat de falses correspondències.
Tradicionalment, l'estimació del moviment d'una càmera està basada en l'aplicació de la geometria epipolar entre cada dues imatges consecutives. No obstant el cas tradicional de la geometria epipolar té algunes limitacions en el cas d'una càmera situada en un robot mòbil. Les diferencies entre dues imatges consecutives són molt petites cosa que provoca inexactituds en el càlcul de matriu fonamental. A més cal resoldre el problema de la correspondència, aquest procés és molt costós en quant a temps de computació i no és gaire efectiu per aplicacions de temps real. En aquestes circumstàncies les tècniques d'estimació del moviment d'una càmera solen basar-se en el flux òptic i en la geometria epipolar diferencial. En la tesi es realitza un recull de totes aquestes tècniques degudament classificades. Aquests mètodes són descrits unificant la notació emprada i es remarquen les
semblances i les diferencies entre el cas discret i el cas diferencial de la geometria epipolar. Per tal de poder aplicar aquests mètodes a l'estimació de moviment d'un robot mòbil, aquest mètodes generals que estimen el moviment d'una càmera amb sis graus de llibertat, han estat adaptats al cas d'un robot mòbil que es desplaça en una superfície plana. Es presenten els resultats obtinguts tant amb el mètodes generals de sis graus de llibertat com amb els adaptats a un robot mòbil utilitzant dades sintètiques i seqüències d'imatges reals.
Aquest tesi finalitza amb una proposta de sistema de localització i de construcció d'un mapa fent servir un sistema estereoscòpic situat en un robot mòbil. Diverses aplicacions de robòtica mòbil requereixen d'un sistema de localització amb l'objectiu de facilitar la navegació del vehicle i l'execució del les trajectòries planificades. La localització es sempre relativa al mapa de l'entorn on el robot s'està movent. La construcció de mapes en un entorn desconegut és una tasca important a realitzar per les futures generacions de robots mòbils. El sistema que es presenta realitza la localització i construeix el mapa de l'entorn de forma simultània. A la tesi es descriu el robot mòbil GRILL, que ha estat la plataforma de treball emprada per aquesta aplicació, amb el sistema de visió estereoscòpic que s'ha dissenyat i s'ha muntat en el robot. També es descriu tots el processos que intervenen en el sistema de localització i construcció del mapa. La implementació d'aquest processos ha estat possible gràcies als estudis realitzats i presentats prèviament (calibració de càmeres, estimació de la matriu fonamental, i estimació del moviment) sense els quals no s'hauria pogut plantejar aquest sistema. Finalment es presenten els mapes en diverses trajectòries realitzades pel robot GRILL en el laboratori.
Les principals contribucions d'aquest treball són:
·Un estat de l'art sobre mètodes de calibració de càmeres. El mètodes són comparats tan des del punt de vista del model de càmera utilitzat com de la precisió dels mètodes.
·Un estudi dels mètodes d'estimació de la matriu fonamental. Totes les tècniques estudiades són classificades i descrites des d'un punt de vista algorísmic.
·Un recull de les tècniques d'estimació del moviment d'una càmera centrat en el mètodes basat en la geometria epipolar diferencial. Aquestes tècniques han estat adaptades per tal d'estimar el moviment d'un robot mòbil.
·Una aplicació de robòtica mòbil per tal de construir un mapa dinàmic de l'entorn i localitzar-se per mitja d'un sistema estereoscòpic. L'aplicació presentada es descriu tant des del punt de vista del maquinari com del programari que s'ha dissenyat i implementat.
Human eyes have been widely studied by the scientific community so that its operation principle is widely known. Computer vision tries to copy the way human beings perceive visual information by means of using cameras acting as eyeballs and computers aspiring to process this information in an --intelligent way". The complex task of being conscious of reality is obviously divided into a set of simpler problems which covers from image acquisition to scene description. One of the main applications is robot perception in which a mobile robot is equipped with a computer vision system. Robots may be able to navigate around an unknown structured environment acquiring visual information of their surroundings with the aim of estimating the position and orientation of every obstacle. Moreover, the pose of the vehicle has to be estimated as accurate as possible. Hence, the motion of the vehicle might be also computed allowing the localization of the vehicle with respect to the 3D map.
This thesis is focused on the study of the geometry involved in stereo vision systems composed by two cameras with the aim of obtaining 3D geometric information of the vehicle surroundings. This objective deals to the study of camera modelling and calibration and the comprehension of the epipolar geometry. Then, the computation of the fundamental matrix of a stereoscopic system is surveyed with the aim of reducing the correspondence problem between both image planes. An accurate estimation of the fundamental matrix allows us not only to compute 3D information of the vehicle environments, but to validate it. Nevertheless, the traditional case of the epipolar geometry has some limitations in the common case of a single camera attached to a mobile robot. Disparities between two consecutive images are rather small at common image rates leading to numerical inaccuracies on the computation of the fundamental matrix. Then, another objective is the study of general vision-based egomotion estimation methods based on the differential epipolar constraint with the aim of perceiving the robot movement instead of its position.
The study of the geometry involved in stereo vision systems leads us to present a computer vision system mounted on a vehicle which navigates in an unknown environment. Two main tasks are faced: a) the localization of the vehicle; and b) the building of an absolute 3D map.
El sistema de visión humano ha sido ampliamente estudiado por la comunidad científica de forma que su principio de funcionamiento es profundamente conocido. La Visión por Computador trata de copiar la forma que nosotros los humanos percibimos la información visual por medio del uso de cámaras actuando como ojos y un ordenador aspirando a procesar toda la información de "forma inteligente". La compleja tarea de ser consciente de la realidad es obviamente dividida en un conjunto de problemas mucho más simples, los cuales abarcan des de la adquisición de la imagen a la descripción de la escena. Una de las numerosas aplicaciones es la percepción por parte de un robot, donde un robot móvil es equipado con un sistema informático de visión por computador. Estos robots deben ser capaces de navegar a lo largo de un entorno estructurado desconocido mediante la adquisición de información visual de su alrededor, con el objetivo de estimar la posición y orientación de todos los obstáculos. Además, la posición del vehículo debe ser estimada de la forma más precisa posible. De esta forma, el movimiento del vehículo puede ser también calculado lo que permite la localización del vehículo con respeto al mapa 3D.
Esta tesis profundiza en el estudio de la geometría existente en los sistemas de visión estéreo compuestos por dos cámaras con la intención de obtener información geométrica 3D del entorno del vehículo. Este objetivo lleva consigo la necesidad inicial de realizar un estudio de modelado de la cámara y calibración, y la compensación de la geometría epipolar. A continuación, el cálculo de la matriz fundamental de un sistema esteresocópico es analizado para reducir el problema de la correspondencia entre ambos planos de la imagen. Una estimación precisa de la matriz fundamental nos permite no solamente obtener la información 3D del entorno, sino también validar la misma. No obstante, la geometría epipolar tradicional sufre algunas limitaciones en el caso de una cámara montada en un robot móvil. La disparidad entre dos imágenes consecutivas es realmente mínima trabajando a velocidad estándar lo que conlleva a errores numéricos en el cálculo de la matriz fundamental. Por esta razón, otro objetivo es el estudio de los métodos de estimación del movimiento basados en la geometría epipolar diferencial con el objetivo de pervivir el movimiento del robot y su posición.
El estudio de la geometría inmersa en los sistemas de visión estéreo nos lleva a presentar un sistema de visión por computador montado en un vehículo capaz de navegar en un entorno desconocido. Dos tareas básicas son consideradas: a) la localización del vehículo; y b) la construcción de un mapa 3D absoluto.

We propose algorithms for organization of images in wide-area sparse-view datasets. In such datasets, if the images overlap in scene content, they are related by wide-baseline geometric transformations. The challenge is to identify these relations even if the images sparingly overlap in their content. The images in a dataset are then grouped into sets of related images with the relations captured in each set as a basal (minimal and foundational) graph structures. Images form the vertices in the graph structure and the edges define the geometric relations between the images. We use these basal graphs for geometric walkthroughs and detection of noisy location (GPS) and orientation (magnetometer) information that may be stored with each image. We have five algorithmic contributions. First, we propose an algorithm BLOGS (Balanced Local and Global Search) that uses a novel hybrid Markov Chain Monte Carlo (MCMC) strategy called 'hop-diffusion' for epipolar geometry estimation between a pair of wide-baseline images that is 10 times faster and more accurate than the state-of-the-art. Hops are global searches and diffusions are local searches. BLOGS is able to handle very wide-baseline views characteristic of wide-area sparse-view datasets. It also produces a geometric match score between an image pair. Second, we propose a photometric match score, the Cumulative Correspondence Score (CCS). The proposed photometric scores are fast approximations of the computationally expensive geometric scores. Third, we use the photometric scores and the geometric scores to find groups of related images and to organize them in the form of basal graph structures using a novel hybrid algorithm we call theCOnnected component DIscovery by Minimally Specifying an Expensive Graph (CODIMSEG). The objective of the algorithm is to minimize the number of geometric estimations and yield results similar to what would be achieved if all-pair geometric matching were done. We compared the performances of the CCS and CODIMSEG algorithms with GIST (means summary of an image) and k-Nearest Neighbor (k-NN) based approaches. We found that CCS and CODIMSEG perform significantly better than GIST and k-NN respectively in identifying visually connected images. Our algorithm achieved more than 95% true positive rate at 0% false positive rate. Fourth, we propose a basal tree graph expansion algorithm to make the basal graphs denser for applications like geometric walk-throughs using the minimum Hamiltonian path algorithm and detection of noisy position (GPS) and orientation (magnetometer) tags. We propose two versions of geometric walkthroughs, one using minimum spanning tree based approximation of the minimum Hamiltonian path on the basal tree graphs and other using the Lin-Kernighan heuristic approximation on the expanded basal graph. Conversion of a non-linear tree structure to a linear path structure leads to discontinuities in path. The Lin-Kernighan algorithm on the expanded basal graphs is shown to be a better approach. Fifth, we propose a vision based geometric voting algorithm to detect noisy GPS and magnetometer tags using the basal graphs. This problem has never been addressed before to the best of our knowledge. We performed our experiments on the Nokia dataset (which has 243 images in the 'Lausanne' dataset and 105 images in the 'Demoset'), ArtQuad dataset (6514 images) and Oxford dataset (5063 images). All the three datasets are very different. Nokia dataset is a very wide-baseline sparse-view dataset. ArtQuad dataset is a wide-baseline dataset with denser views compared to the Nokia dataset. Both these datasets have GPS tagged images. Nokia dataset has magnetometer tags too. ArtQuad dataset has 348 images with the commercial GPS information as well as high precision differential GPS data which serves as ground truth for our noisy tag detection algorithm. Oxford dataset is a wide-baseline dataset with plenty of distracters that test the algorithm's capability to group images correctly. The larger datasets test the scalability of our algorithms. Visually inspected feature matches and image matches were used as ground truth in our experiments. All the experiments were done on a single PC.

La visione è il processo cerebrale mediante il quale l'organismo umano riesce a estrarre informazioni dal dato visivo proveniente dalla retina. Tentare di imitare questo comportamento mediante un elaboratore elettronico, il cosiddetto problema della visione, è una delle maggiori sfide del XXI secolo. In questo contesto lo scopo della tesi è dare una descrizione degli strumenti matematici che permettono di modellizzare la visione stereoscopica ed esporre le condizioni sotto le quali sia possibile effettuare una ricostruzione 3D ambientale a partire da due immagini della stessa scena nell'ipotesi di assenza di errore.

Existing systems of scene reconstruction and theorethical basics necessary for scene reconstruction from images data are described in this work. System of scene reconstruction from video was designed and implemented. Its results were analyzed and possible future work was proposed. OpenCV, ArtToolKit and SIFT libraries which were used in this project are also described.

This master-thesis presents an approach to track and count the number of fruit incommercial mango orchards. The algorithm is intended to enable precision agri-culture and to facilitate labour and post-harvest storage planning. The primary objective is to develop an multi-view algorithm and investigate how it can beused to mitigate the effects of visual occlusion, to improve upon estimates frommethods that use a single central or two opposite viewpoints. Fruit are detectedin images by using two classification methods: dense pixel-wise cnn and regionbased r-cnn detection. Pair-wise fruit correspondences are established between images by using geometry provided by navigation data, and lidar data is used to generate image masks for each separate tree, to isolate fruit counts to individual trees. The tracked fruit are triangulated to locate them in 3D space, and spatial statistics are calculated over whole orchard blocks. The estimated tree counts are compared to single view estimates and validated against ground truth data of 16 mango trees from a Bundaberg mango orchard in Queensland, Australia. The results show a high R2-value of 0.99335 for four hand labelled trees and a highest R2-value of 0.9165 for the machine labelled images using the r-cnn classifier forthe 16 target trees.

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.

This work describes 3D reconstruction using stereo vision. It presents methods for automatic localization of corresponding points in both images and their reprojection into 3D space. Application created can be used for navigation of a robot and object avoidance. Second part of the document describes chosen components of the robot. Path finding algorithms are also discussed, particulary Voronoi's diagram.

För att kunna rekonstruera en tredimensionell volym av en hjärna avbildad med hjälp av magnetresonanstomografi (MRI) behöver man korrigera varje snittbild i förhållande till varandra, beroende på oundvikliga rörelser hos den röntgade patienten. Detta förfarande kallas bildregistrering och idag använder man sig primärt av en metod där en bild utses till referensbild och därefter anpassas närliggande bilder, som antas ha en minimal avvikelse, till referensen.

Syftet med detta examensarbete är att använda en annan metod vanligen utnyttjad inom datorseende för att estimera ett rörelsefält utifrån en vanlig videosekvens, genom att följa markörer som indikerar rörelse. Målet är att skapa en robust estimering av huvudets rörelse, som då kan användas för att skapa en mer noggrann korrigering och därmed också en bättre rekonstruktion.

Before reconstructing a three dimensional volume from an MR brain imaging sequence there is a need for aligning each slice, due to unavoidable movement of the patient during the scanning. This procedure is known as image registration and the method used primarily today is based on a selected slice being the reference slice and then registrating the neighbouring slices, which are assumed to be of minimal deviation.

The purpose of this thesis is to use another method commonly used in computer vision - to estimate the motion from a regular videosequence, by tracking markers indicating movement. The aim is to create a robust estimation of the movement of the head, which in turn can be used to create a more accurate alignment and volume.

The main goal of this master’s thesis was get up used methods for observation the stereoscopic scene with one couple of cameras and find out good solving for processing these resulting pictures for two-view and multiple-view autostereoscopic displays for three-dimensional perception. For methods for acquisition video was introduced two methods. They were method “Off-axis” with parallel camera axis and method “Toe in” with intersections axis. For fit method was choice the method named as “Off-axis“. It was not produces the vertical parallax and in detail was in this work described principle of this method. Further were describe principles off used methods for three-dimensional perception namely from the oldest method named anaglyph after methods for viewing at autostereoscopic displays. The Autostereoscopic displays were main goal of this thesis and so their principles were described in details. For production the result image for autostereoscopic displays was used generation intermediate images between left and right camera. Resulting videos were acquisition for testing scene in created in 3D studio Blender, where was possible setting system of cameras exactly parallel axis. Then were introduce principles processing video where was extract from the couple of cameras where were connected to PC for help digitizing card and next time with two web cameras. Here is not guaranteed exact parallel axis system. Therefore this work try for real cameras achieve exactly parallel axis system by the help of transformations of frames with stereo rectification. Stereo rectification was solving with OpenCV libraries and was used two methods. Both methods work from principles epipolar geometry that was described in this work also in detail. First method rectifies pictures on the basis fundamental matrix and found correspondences points in two images of the scene and second method rectifies pictures from knowledge intrinsic and extrinsic parameters of stereoscopic system of cameras. In the end of this work was described application for implementation introduced methods.

This master's thesis will take us through theoretical procedure that allows us to determine the distance of an object by stereoscopic sensor. Part of this work presents the description of the steps to achieve image of objects, calibraton and rectification. At the next part our study provides an overview of algortihms for creating disparity maps and determining the distance of the object from sensor. In the following part of thesis deals with the implementation of these processes into aplication which aim is to measure the distance.

Abstract : Images acquired from unmanned aerial vehicles (UAVs) can provide data with unprecedented spatial and temporal resolution for three-dimensional (3D) modeling. Solutions developed for this purpose are mainly operating based on photogrammetry concepts, namely UAV-Photogrammetry Systems (UAV-PS). Such systems are used in applications where both geospatial and visual information of the environment is required. These applications include, but are not limited to, natural resource management such as precision agriculture, military and police-related services such as traffic-law enforcement, precision engineering such as infrastructure inspection, and health services such as epidemic emergency management. UAV-photogrammetry systems can be differentiated based on their spatial characteristics in terms of accuracy and resolution. That is some applications, such as precision engineering, require high-resolution and high-accuracy information of the environment (e.g. 3D modeling with less than one centimeter accuracy and resolution). In other applications, lower levels of accuracy might be sufficient, (e.g. wildlife management needing few decimeters of resolution). However, even in those applications, the specific characteristics of UAV-PSs should be well considered in the steps of both system development and application in order to yield satisfying results. In this regard, this thesis presents a comprehensive review of the applications of unmanned aerial imagery, where the objective was to determine the challenges that remote-sensing applications of UAV systems currently face. This review also allowed recognizing the specific characteristics and requirements of UAV-PSs, which are mostly ignored or not thoroughly assessed in recent studies. Accordingly, the focus of the first part of this thesis is on exploring the methodological and experimental aspects of implementing a UAV-PS. The developed system was extensively evaluated for precise modeling of an open-pit gravel mine and performing volumetric-change measurements. This application was selected for two main reasons. Firstly, this case study provided a challenging environment for 3D modeling, in terms of scale changes, terrain relief variations as well as structure and texture diversities. Secondly, open-pit-mine monitoring demands high levels of accuracy, which justifies our efforts to improve the developed UAV-PS to its maximum capacities. The hardware of the system consisted of an electric-powered helicopter, a high-resolution digital camera, and an inertial navigation system. The software of the system included the in-house programs specifically designed for camera calibration, platform calibration, system integration, onboard data acquisition, flight planning and ground control point (GCP) detection. The detailed features of the system are discussed in the thesis, and solutions are proposed in order to enhance the system and its photogrammetric outputs. The accuracy of the results was evaluated under various mapping conditions, including direct georeferencing and indirect georeferencing with different numbers, distributions and types of ground control points. Additionally, the effects of imaging configuration and network stability on modeling accuracy were assessed. The second part of this thesis concentrates on improving the techniques of sparse and dense reconstruction. The proposed solutions are alternatives to traditional aerial photogrammetry techniques, properly adapted to specific characteristics of unmanned, low-altitude imagery. Firstly, a method was developed for robust sparse matching and epipolar-geometry estimation. The main achievement of this method was its capacity to handle a very high percentage of outliers (errors among corresponding points) with remarkable computational efficiency (compared to the state-of-the-art techniques). Secondly, a block bundle adjustment (BBA) strategy was proposed based on the integration of intrinsic camera calibration parameters as pseudo-observations to Gauss-Helmert model. The principal advantage of this strategy was controlling the adverse effect of unstable imaging networks and noisy image observations on the accuracy of self-calibration. The sparse implementation of this strategy was also performed, which allowed its application to data sets containing a lot of tie points. Finally, the concepts of intrinsic curves were revisited for dense stereo matching. The proposed technique could achieve a high level of accuracy and efficiency by searching only through a small fraction of the whole disparity search space as well as internally handling occlusions and matching ambiguities. These photogrammetric solutions were extensively tested using synthetic data, close-range images and the images acquired from the gravel-pit mine. Achieving absolute 3D mapping accuracy of 11±7 mm illustrated the success of this system for high-precision modeling of the environment.
Résumé : Les images acquises à l’aide d’aéronefs sans pilote (ASP) permettent de produire des données de résolutions spatiales et temporelles uniques pour la modélisation tridimensionnelle (3D). Les solutions développées pour ce secteur d’activité sont principalement basées sur des concepts de photogrammétrie et peuvent être identifiées comme des systèmes photogrammétriques embarqués sur aéronefs sans pilote (SP-ASP). Ils sont utilisés dans plusieurs applications environnementales où l’information géospatiale et visuelle est essentielle. Ces applications incluent notamment la gestion des ressources naturelles (ex. : agriculture de précision), la sécurité publique et militaire (ex. : gestion du trafic), les services d’ingénierie (ex. : inspection de bâtiments) et les services de santé publique (ex. : épidémiologie et gestion des risques). Les SP-ASP peuvent être subdivisés en catégories selon les besoins en termes de précision et de résolution. En effet, dans certains cas, tel qu’en ingénierie, l’information sur l’environnement doit être de haute précision et de haute résolution (ex. : modélisation 3D avec une précision et une résolution inférieure à un centimètre). Pour d’autres applications, tel qu’en gestion de la faune sauvage, des niveaux de précision et de résolution moindres peut être suffisants (ex. : résolution de l’ordre de quelques décimètres). Cependant, même dans ce type d’applications les caractéristiques des SP-ASP devraient être prises en considération dans le développement des systèmes et dans leur utilisation, et ce, pour atteindre les résultats visés. À cet égard, cette thèse présente une revue exhaustive des applications de l’imagerie aérienne acquise par ASP et de déterminer les challenges les plus courants. Cette étude a également permis d’établir les caractéristiques et exigences spécifiques des SP-ASP qui sont généralement ignorées ou partiellement discutées dans les études récentes. En conséquence, la première partie de cette thèse traite des aspects méthodologiques et d’expérimentation de la mise en place d’un SP-ASP. Le système développé a été évalué pour la modélisation précise d’une gravière et utilisé pour réaliser des mesures de changement volumétrique. Cette application a été retenue pour deux raisons principales. Premièrement, ce type de milieu fournit un environnement difficile pour la modélisation, et ce, en termes de changement d’échelle, de changement de relief du terrain ainsi que la grande diversité de structures et de textures. Deuxièment, le suivi de mines à ciel ouvert exige un niveau de précision élevé, ce qui justifie les efforts déployés pour mettre au point un SP-ASP de haute précision. Les composantes matérielles du système consistent en un ASP à propulsion électrique de type hélicoptère, d’une caméra numérique à haute résolution ainsi qu’une station inertielle. La composante logicielle est composée de plusieurs programmes développés particulièrement pour calibrer la caméra et la plateforme, intégrer les systèmes, enregistrer les données, planifier les paramètres de vol et détecter automatiquement les points de contrôle au sol. Les détails complets du système sont abordés dans la thèse et des solutions sont proposées afin d’améliorer le système et la qualité des données photogrammétriques produites. La précision des résultats a été évaluée sous diverses conditions de cartographie, incluant le géoréférencement direct et indirect avec un nombre, une répartition et des types de points de contrôle variés. De plus, les effets de la configuration des images et la stabilité du réseau sur la précision de la modélisation ont été évalués. La deuxième partie de la thèse porte sur l’amélioration des techniques de reconstruction éparse et dense. Les solutions proposées sont des alternatives aux techniques de photogrammétrie aérienne traditionnelle et adaptée aux caractéristiques particulières de l’imagerie acquise à basse altitude par ASP. Tout d’abord, une méthode robuste de correspondance éparse et d’estimation de la géométrie épipolaire a été développée. L’élément clé de cette méthode est sa capacité à gérer le pourcentage très élevé des valeurs aberrantes (erreurs entre les points correspondants) avec une efficacité de calcul remarquable en comparaison avec les techniques usuelles. Ensuite, une stratégie d’ajustement de bloc basée sur l’intégration de pseudoobservations du modèle Gauss-Helmert a été proposée. Le principal avantage de cette stratégie consistait à contrôler les effets négatifs du réseau d’images instable et des images bruitées sur la précision de l’autocalibration. Une implémentation éparse de cette stratégie a aussi été réalisée, ce qui a permis de traiter des jeux de données contenant des millions de points de liaison. Finalement, les concepts de courbes intrinsèques ont été revisités pour l’appariement stéréo dense. La technique proposée pourrait atteindre un haut niveau de précision et d’efficacité en recherchant uniquement dans une petite portion de l’espace de recherche des disparités ainsi qu’en traitant les occlusions et les ambigüités d’appariement. Ces solutions photogrammétriques ont été largement testées à l’aide de données synthétiques, d’images à courte portée ainsi que celles acquises sur le site de la gravière. Le système a démontré sa capacité a modélisation dense de l’environnement avec une très haute exactitude en atteignant une précision 3D absolue de l’ordre de 11±7 mm.

Thesis (M.S. in Computer Science)--Naval Postgraduate School, September 2007.
Thesis Advisor(s): Kölsch, Mathias ; Squire, Kevin. "September 2007." Description based on title screen as viewed on October 24, 2007. Includes bibliographical references (p. 169-171). Also available in print.

In this thesis, opti-acoustic stereo imaging, which is the deployment of two-dimensional (2D) high frequency imaging sonar with the electro-optical camera in calibrated stereo configuration, is studied. Optical cameras give detailed images in clear waters. However, in dark or turbid waters, information coming from electro-optical sensor is insufficient for accurate scene perception. Imaging sonars, also known as acoustic cameras, can provide enhanced target details under these scenarios. To illustrate these visibility conditions, a 2D high frequency imaging sonar simulator as well as an underwater optical image simulator is developed. A computationally efficient algorithm is also proposed for the post-processing of the returned sonar signals. Where optical visibility allows, integration of the sonar and optical images effectively provides binocular stereo vision capability and enables the recovery of three-dimensional (3D) structural information. This requires solving the feature correspondence problem for these completely different sensing modalities. Geometrical interpretation of this problem is examined on the simulated optical and sonar images. Matching the features manually, 3D reconstruction performance of opti-acoustic system is also investigated. In addition, motion estimation from opti-acoustic image sequences is studied. Finally, a method is proposed to improve the degraded optical images with the help of sonar images. First, a nonlinear mapping is found to match local the features in opti-acoustical images. Next, features in the sonar image is mapped to the optical image using the transformation. Performance of the mapping is evaluated for different scene geometries.

Virtual reality systems are nowadays common part of many research institutes due to its low cost and effective visualization of data. They mostly allow visualization and exploration of virtual worlds, but many lack user interaction. In this paper we suggest multi-camera optical system, which allows effective user interaction, thereby increasing immersion of virtual system. This paper describes the calibration process of multiple cameras using point correspondences.

This thesis deals with reconstruction of golf ball position using multiple cameras. Reconstruction will be used for golf simulator project. System is using fotogrametric calibration and triangulation algorithm for obtaing point coordinates. Work also discuss options for camera selection. The result is making of prototype of the simulator.

The Master thesis is focused on analyzing stereo camera ZED in the outdoor environment. There is compared ZEDfu visual odometry with commonly used methods like GPS or wheel odometry. Moreover, the thesis includes analyses of SLAM in the changeable outdoor environment, too. The simultaneous mapping and localization in RTAB-Map were processed separately with SIFT and BRISK descriptors. The aim of this master thesis is to analyze the behaviour ZED camera in the outdoor environment for future implementation in mobile robotics.

Feature matching in images plays an important role in computer vision such as for 3D reconstruction, motion analysis, object recognition, target tracking and dynamic scene analysis. In this paper, we present a robust cooperative strategy to establish the correspondence of the contours between two uncalibrated images based on the recovered epipolar geometry. We take into account two representations of contours in image as contour points and contour chains. The method proposed in the paper is composed of the following two consecutive steps: (1) The first step uses the LMedS method to estimate the fundamental matrix based on Hartley’s 8-point algorithm, (2) The second step uses a new robust cooperative strategy to match contours. The presented approach has been tested with various real images and experimental results show that our method can produce more accurate contour correspondences.
Singapore-MIT Alliance (SMA)

Recovering three-dimensional information from two-dimensional images is the fundamental goal of stereo techniques. The problem of recovering depth (three-dimensional information) from a set of images is essentially the correspondence problem: Given a point in one image, find the corresponding point in each of the other images. Finding potential correspondences usually involves matching some image property. If the images are from nearby positions, they will vary only slightly, simplifying the matching process. Once a correspondence is known, solving for the depth is simply a matter of geometry. Real images are composed of noisy, discrete samples, therefore the calculated depth will contain error. This error is a function of the baseline or distance between the images. Longer baselines result in more precise depths. This leads to a conflict: short baselines simplify the matching process, but produce imprecise results; long baselines produce precise results, but complicate the matching process. In this paper, we present a method for generating dense depth maps from large sets (1000's) of images taken from arbitrary positions. Long baseline images improve the accuracy. Short baseline images and the large number of images greatly simplifies the correspondence problem, removing nearly all ambiguity. The algorithm presented is completely local and for each pixel generates an evidence versus depth and surface normal distribution. In many cases, the distribution contains a clear and distinct global maximum. The location of this peak determines the depth and its shape can be used to estimate the error. The distribution can also be used to perform a maximum likelihood fit of models directly to the images. We anticipate that the ability to perform maximum likelihood estimation from purely local calculations will prove extremely useful in constructing three dimensional models from large sets of images.

碩士
國立高雄大學
資訊工程學系碩士班
102
Recently, as 3D related technologies rapidly gained popularity, different 3D data acquisition devices are also being constructed and developed. Many such devices are only able to acquire the data at a particular location and time, since they are unable to determine the ego-motion. Thus it is almost impossible to associate data acquired at different locations or time frames to form more complete 3D information. In this research, we utilize the binocular stereo data provided by the KITTI Vision Benchmark Suite for 3D ego-motion estimation. The Speeded Up Robust Features method is applied to detect feature points and generate the descriptors from calibrated binocular stereo images. Afterwards, Semi-Global Matching is performed and integrated with camera parameters to calculate the 3D coordinates of the selected feature points. During the feature tracking stage, selected feature points are first matched temporally. The 3D coordinates, 2D reprojections and camera parameters are combined through the Efficient Perspective-n-Point Camera Pose Estimation algorithm to estimate the motion of the camera. Finally, a two-stage Sparse Bundle Adjustment method is applied to perform fast global adjustment and avoid local optimal results. Since the accuracy of motion estimation is directly related to feature tracking, this research also focuses on the accuracy of feature tracking. Epipolar geometry and stereo matching disparity are combined to propose an adaptive approach using angular and length parameters as limiting criteria. The method is able to increase the matching accuracy and improve ego-motion estimation. Experiment results have shown that over each meter of movement, the proposed method has on average a translation error of 2 percent and a rotation error of 0.008 degrees per meter.

碩士
國立成功大學
電腦與通信工程研究所
96
After availability of multiview stereo LCD display systems, people can perceive stereo videos without wearing any special 3D glasses. The multiview video coding (MVC) system is a newly-developed video compression standard in recent years. This video compression standard is expected to be the key technology in the 3D stereo multimedia applications. This standard, named H.264/MVC is an extension of H.264/AVC. In this thesis, we propose a new prediction method to predict the adaptive global disparity vector (GDV) in the MVC system. We also improve the current fast disparity search algorithm in H.264/AVC by incorporating the characteristics among multi-views and the new GDV prediction method.

Cette thèse porte sur deux sujets de vision par ordinateur axés sur l’analyse de mouvement dans une scène dynamique vue par une ou plusieurs caméras. En premier lieu, nous avons travaillé sur le problème de la capture de mouvement avec des caméras non synchronisées. Ceci entraı̂ne généralement des erreurs de mise en correspondance 2D et par la suite des erreurs de reconstruction 3D. En contraste avec les solutions matérielles déjà existantes qui essaient de minimiser voire annuler le délai temporel entre les caméras, nous avons proposé une solution qui assure une invariance aux délais. En d’autres termes, nous avons développé une méthode qui permet de trouver la bonne mise en correspondance entre les points à reconstruire indépendamment du délai temporel. En second lieu, nous nous sommes intéressés au problème du flux optique avec une approche différente des méthodes proposées dans l’état de l’art. Le flux optique est utilisé pour l’analyse de mouvement en temps réel. Il est donc important qu’il soit calculé rapidement. Généralement, les méthodes existantes de flux optique sont classées en deux principales catégories: ou bien à la fois denses et précises mais très exigeantes en calcul, ou bien rapides mais moins denses et moins précises. Nous avons proposé une alternative qui tient compte à la fois du temps de calcul et de la précision du résultat. Nous avons proposé d’utiliser les isocontours d’intensité et de les mettre en correspondance afin de retrouver le flux optique en question. Ces travaux ont amené à deux principales contributions intégrées dans les chapitres de la thèse.
In this thesis we focused on two computer vision subjects. Both of them concern motion analysis in a dynamic scene seen by one or more cameras. The first subject concerns motion capture using unsynchronised cameras. This causes many correspondence errors and 3D reconstruction errors. In contrast with existing material solutions trying to minimize the temporal delay between the cameras, we propose a software solution ensuring an invariance to the existing temporal delay. We developed a method that finds the good correspondence between points regardless of the temporal delay. It solves the resulting spatial shift and finds the correct position of the shifted points. In the second subject, we focused on the optical flow problem using a different approach than the ones in the state of the art. In most applications, optical flow is used for real-time motion analysis. It is then important to be performed in a reduced time. In general, existing optical flow methods are classified into two main categories: either precise and dense but computationally intensive, or fast but less precise and less dense. In this work, we propose an alternative solution being at the same time, fast and precise. To do this, we propose extracting intensity isocontours to find corresponding points representing the related optical flow. By addressing these problems we made two major contributions.

碩士
國立中央大學
通訊工程研究所
97
In recent years, various applications of multi-view video provide viewers a new viewing experience. Accordingly, multi-view video coding (MVC) plays a key role in transmission and storage of multi-view videos. However, besides temporal prediction which is used to reduce temporal redundancy, the MVC encoder also explores the inter-view redundancy by inter-view prediction. Because of the optimal decision of inter-view prediction and temporal prediction, the heavy computational load results in the difficulty of its realization in real-time systems. Therefore, this paper proposes a fast algorithm for the MVC encoder. There are two parts of our proposed scheme, fast inter frame direction predictor and epipolar geometry based inter-view prediction. The fast inter frame direction predictor decides the prediction direction that the current block may prefer, according to the motion characteristic of the current block inferred from the blocks in the neighboring frames. The epipolar geometry based inter-view prediction improves the accuracy of the location of matching blocks. Our experimental results show that the fast inter frame direction predictor reduces 15% to 24% of encoding time. By combining it with epipolar geometry based inter-view prediction, there is 20% to 28% of encoding time is reduced with the bitrate reduction ranging from 0.6% to 8.0%.

No
An algorithm for the rectification of uncalibrated images is presented and applied to a variety of cases. The algorithm generates the rectifying transformations directly from the geometrical relationship between the images, using any three correspondences in the images to define a reference plane. A small set of correspondences is used to calculate an initial rectification. Additional correspondences are introduced semi-automatically, by correlating regions of the rectified images. Since the rectified images of surfaces in the reference plane have no relative distortion, features can be matched very accurately by correlation, allowing small changes in disparity to be detected. In the 3-d reconstruction of an architectural scene, differences in depth are resolved to about 0.001 of the distance from camera to subject.

This dissertation describes the design and implementation of a system that has been designed to extract 3D information from pairs of 2D images. System input consists of two images taken by an ordinary digital camera. System output is a full 3D model extracted from 2D images. There are no assumptions about the positions of the cameras during the time when the images are being taken, but the scene must not undergo any modifications. The process of extracting 3D information from 2D images consists of three basic steps. First, point matching is performed. The main contribution of this step is the introduction of an approach to matching image segments in the context of an approximation space. The second step copes with the problem of estimating external camera parameters. The proposed solution to this problem uses 3D geometry rather than the fundamental matrix widely used in 2D to 3D conversion. In the proposed approach (DirectGS), the distances between reprojected rays for all image points are minimised. The contribution of the approach considered in this step is a definition of an optimal search space for solving the 2D to 3D conversion problem and introduction of an efficient algorithm that minimises reprojection error. In the third step, the problem of dense matching is considered. The contribution of this step is the introduction of a proposed approach to dense matching of 3D object structures that utilises the presence of points on lines in 3D space. The theory and experiments developed for this dissertation demonstrate the usefulness of the proposed system in the process of digitizing 3D information. The main advantage of the proposed approach is its low cost, simplicity in use for an untrained user and the high precision of reconstructed objects.
October 2007

Ένας από τους παράγοντες που ενοχοποιούνται για την ανάπτυξη ινομυϊκής υπερπλασίας στη φλεβική αναστόμωση των συνθετικών αρτηριοφλεβικών μοσχευμάτων, είναι η διαταραχή των αιμοδυναμικών συνθηκών στην περιοχή της αναστόμωσης. Για τον υπολογισμό της ροής, δηλαδή των πεδίων ταχύτητας, διατμητικής τάσης και στροβιλισμού, στην περιοχή αυτή, χρησιμοποιούνται μέθοδοι της υπολογιστικής δυναμικής των ρευστών, οι οποίες προϋποθέτουν γνώση της τριδιάστατης γεωμετρίας των αγγείων και του μοσχεύματος. Στην παρούσα διπλωματική εργασία αναπτύσσεται μια μεθοδολογία και ο αντίστοιχος αλγόριθμος για τον προσδιορισμό της τριδιάστατης γεωμετρίας της κεντρικής γραμμής των αγγείων από διεπίπεδη αγγειογραφία, όπου η σχέση των δύο συστημάτων αναφοράς θεωρείται άγνωστη, καθώς και για τη σχεδίαση κυκλικών διατομών σε επιλεγμένες θέσεις για την προσέγγιση του αγγειακού αυλού. Η μέθοδος βασίζεται στην θεωρία των Metz – Fencil (1989) και απαιτεί την εκ των προτέρων γνώση δύο ζευγών αντίστοιχων σημείων στις προβολές για τον προσδιορισμό της σχέσης που συνδέει τα δύο συστήματα αναφοράς. Για την αναγνώριση αντίστοιχων σημείων στις προβολές χρησιμοποιείται η τεχνική της επιπολικής γραμμής, ενώ η ανακατασκευή της κεντρικής γραμμής πραγματοποιείται με χρήση παραμετρικής φυσικής spline. Πραγματοποιήθηκε έλεγχος της μεθόδου με χρήση πρότυπης γεωμετρίας και διαπιστώθηκε ότι η ακρίβεια της ανακατασκευής εξαρτάται από το πλήθος και την ποιότητα των σημείων ελέγχου της spline. Τελικά, η μέθοδος εφαρμόστηκε σε πρότυπο αντικείμενο, γνωστής γεωμετρίας, ανάλογης αυτής που λαμβάνεται σε πραγματικές αγγειογραφικές προβολές αρτηριοφλεβικής αναστόμωσης στην περιοχή της καρωτίδας και διαπιστώθηκε ότι ανακατασκευάζει με καλή ακρίβεια την κεντρική γραμμή του αντικειμένου.
One of the factors that have been incriminated for the growth of fibromuscular hyperplasia at the anastomosis of the synthetic arteriovenous implant, is the disturbance of the hemodynamic conditions at the region of the anastomosis. For the computation of the flow at this region, that is the fields of velocity, shear stress and rotation, methods of computational flow dynamics are used, which require that the 3D geometry of the vessels and the implant are known in advance. In this thesis, we developed a methodology and the respective algorithm for the determination of the 3D geometry of the central line of the vessels from biplane angiography, for which the relation of the two systems of coordinates are unknown, as well as for the drawing of circular cross section at selected positions for approximation of arterial lumen. The method is based on the theory of C.E.Metz and L.E.Fencil (1989) and requires the knowledge of two pairs of respective points on the views in advanced in order to calculate the rotation matrix and the translation vector that relate the two systems of coordinates. For recognition of respective points on the two views the epipolar line technique is being used, while the central line is reconstructed using a parametric natural spline. The method was tested using a model and it showed that the accuracy of the reconstruction depends on the number and the quality of the control points of the spline. Finally, the method was implemented on a model object with geometry, analogous to that we get from real angiographic views of arteriovenous anastomosis at the region of the carotid artery, and its central line was reconstructed with very good accuracy.

Κατά τη διάρκεια της διπλωματικής εργασίας μελετήθηκαν συστήματα οπτικού προσανατολισμού. Έγινε μελέτη των μεθόδων οπτικού προσανατολισμού που στηρίζονται στην επίλυση του προβλήματος της επιπολικής γεωμετρίας. Πιο συγκεκριμένα έγινε μελέτη των σύγχρονων μεθόδων επίλυσης του προβλήματος της επιπολικής γεωμετρίας (μέθοδοι 5,7 και 8 σημείων). Παράλληλα έγινε μελέτη αλγορίθμων RANSAC για να εξασφαλιστεί η σθεναρότητα του συστήματος. Τα παραπάνω συστήματα υλοποιήθηκαν σε βιβλιοθήκες λογισμικού σε γλώσσα C++ με δυνατότητα απευθείας χρήσης τους από το περιβάλλον Labview. Αντίστοιχη μελέτη, ανάπτυξη και υλοποίηση έγινε και για το σύστημα απόλυτου προσανατολισμού που χρησιμοποιεί σημεία με γνωστές συντεταγμένες. Στη συνέχεια τα συστήματα που αναπτύχθηκαν αξιολογήθηκαν με χρήση συνθετικών δεδομένων. Τέλος διεξήχθη πειραματική αξιολόγηση του συστήματος που αναπτύχθηκε με πραγματικά δεδομένα μέσω της χρήσης μιας πειραματικής διάταξης όπου η κάμερα είναι προσαρτημένη σε μία διάταξη Pan-Tilt, ενώ προτάθηκαν και τρόποι βελτίωσης της ακρίβειας του συστήματος οπτικού προσανατολισμού.
During the diploma thesis, vision-only navigational systems have been studied. Firstly, the epipolar geometry methods (5,7 and 8 points) have been studied in depth. Secondly, a RANSAC framework have been developed to ensure the robustness of the system’s measures. The above systems have been implemented, using the C++ programming language, into software libraries that can be used by the Labview enviroment. Moreover vision-only absolute orientation systems that use landmarks have been developed and implemented. Then the systems developed were evaluated using synthetic data. Finally the system that have been developed was evaluated with real data using an experimental setup where the camera is attached to a Pan-Tilt unit,and ways of improving the vision-only navigational system have been proposed.

Cette these concerne principalement la reconstruction tridimensionnelle a partir d'images issues de cameras non etalonnees. Deux autres sujets lies a la reconstruction ont ete traites : le calcul de la geometrie epipolaire et la mise en correspondance des points dans les images. Nous nous placons dans le cas general d'une sequence d'images obtenues avec une ou plusieurs cameras de carateristiques inconnues. Quand seuls les points observes dans les images sont utilisees la seule reconstruction possible est de type projective. Nous proposons d'abord une methode pour calculer la reconstruction projective, ensuite, montrons comment passer d'une telle reconstruction a une reconstruction euclidienne. Ce passage utilise des contraintes euclidiennes issues de connaissances a priori sur la scene tridimensionnelle. Enfin, nous proposons une methode de reconstruction euclidienne lorsque les parametres intrinseques des cameras sont approximativement connus. Cette methode utilise un parametrage permettant une grande stabilite dans les calculs Toutes les methodes proposees sont validees avec des exemples d'images reelles ou simulees.

Humans can perceive three dimension, our world is three dimensional and it is becoming increasingly digital too. We have the need to capture and preserve our existence in digital means perhaps due to our own mortality. We have also the need to reproduce objects or create small identical objects to prototype, test or study them. Some objects have been lost through time and are only accessible through old photographs. With robust model generation from photographs we can use one of the biggest human data sets and reproduce real world objects digitally and physically with printers. What is the current state of development in three dimensional reconstruction through photographs both in the commercial world and in the open source world? And what tools are available for a developer to build his own reconstruction software? To answer these questions several pieces of software were tested, from full commercial software packages to open source small projects, including libraries aimed at computer vision. To bring to the real world the 3D models a 3D printer was built, tested and analyzed, its problems and weaknesses evaluated. Lastly using a computer vision library a small software with limited capabilities was developed.