Thesis (Ph.D.)--Drexel University, 2009. / Includes abstract and vita. Includes bibliographical references (leaves 81-84).

Thesis (Ph.D.)--Drexel University, 2009. / Includes abstract and vita. Includes bibliographical references (leaves 58-60).

This thesis introduces the use of catadioptrics for multidimensional interaction in the approach called Reflections. In computer graphics there is a need for multidimensional interaction that is not restricted by cabling connected to the input device. The use of a camera and computer vision presents a solution to the cabling problem. Unfortunately this solution presents an equally challenging problem: a single camera alone can not accurately calculate depth and is therefore not suitable for multidimensional interaction. This thesis presents a solution, called reflections to this problem. Reflections makes use of only a single camera and one or more mirrors to accurately calculate 3D, 5D, and 6D information in real time. Two applications in which this approach is used for natural, non-intrusive and multidimensional interaction are the Virtual Drums Project and Ndebele painting in virtual reality. The interaction in these applications and in particular the Virtual Drums is appropriate and intuitive, e.g. the user plays the drums with a real drumstick. Several computer vision algorithms are described in this thesis, which are used in the implementation of the Virtual Drums Project. / Dissertation (MSc ( Computer Science))--University of Pretoria, 2005. / Computer Science / unrestricted

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第21910号 / 情博第693号 / 新制||情||119(附属図書館) / 京都大学大学院情報学研究科知能情報学専攻 / (主査)講師 延原 章平, 教授 西野 恒, 准教授 飯山 将晃 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

Ce manuscrit étudie les images omnidirectionnelles catadioptriques couleur en tant que variétés Riemanniennes. Cette représentation géométrique ouvre des pistes intéressantes pour résoudre les problèmes liés aux distorsions introduites par le système catadioptrique dans le cadre de la perception couleur des systèmes autonomes. Notre travail démarre avec un état de l’art sur la vision omnidirectionnelle, les différents dispositifs et modèles de projection géométriques. Ensuite, nous présentons les notions de base de la géométrie Riemannienne et son utilisation en traitement d’images. Ceci nous amène à introduire les opérateurs différentiels sur les variétés Riemanniennes, qui nous seront utiles dans cette étude. Nous développons alors une méthode de construction d’un tenseur métrique hybride adapté aux images catadioptriques couleur. Ce tenseur a la double caractéristique, de dépendre de la position géométrique des points dans l’image, et de leurs coordonnées photométriques également. L’exploitation du tenseur métrique proposé pour différents traitements des images catadioptriques, est une partie importante dans cette thèse. En effet, on constate que la fonction Gaussienne est au cœur de plusieurs filtres et opérateurs pour diverses applications comme le débruitage, ou bien l’extraction des caractéristiques bas niveau à partir de la représentation dans l’espace-échelle Gaussien. On construit ainsi un nouveau noyau Gaussien dépendant du tenseur métrique Riemannien. Il présente l’avantage d’être applicable directement sur le plan image catadioptrique, également, variable dans l’espace et dépendant de l’information image locale. Dans la dernière partie de cette thèse, nous discutons des applications robotiques de la métrique hybride, en particulier, la détection de l’espace libre navigable pour un robot mobile, et nous développons une méthode de planification de trajectoires optimal. / This manuscript investigates omnidirectional catadioptric color images as Riemannian manifolds. This geometric representation offers insights into the resolution of problems related to the distortions introduced by the catadioptric system in the context of the color perception of autonomous systems. The report starts with an overview of the omnidirectional vision, the different used systems, and the geometric projection models. Then, we present the basic notions and tools of Riemannian geometry and its use in the image processing domain. This leads us to introduce some useful differential operators on Riemannian manifolds. We develop a method of constructing a hybrid metric tensor adapted to color catadioptric images. This tensor has the dual characteristic of depending on the geometric position of the image points and their photometric coordinates as well.In this work, we mostly deal with the exploitation of the previously constructed hybrid metric tensor in the catadioptric image processing. Indeed, it is recognized that the Gaussian function is at the core of several filters and operators for various applications, such as noise reduction, or the extraction of low-level characteristics from the Gaussian space- scale representation. We thus build a new Gaussian kernel dependent on the Riemannian metric tensor. It has the advantage of being applicable directly on the catadioptric image plane, also, variable in space and depending on the local image information. As a final part in this thesis, we discuss some possible robotic applications of the hybrid metric tensor. We propose to define the free space and distance transforms in the omni- image, then to extract geodesic medial axis. The latter is a relevant topological representation for autonomous navigation, that we use to define an optimal trajectory planning method.

Thesis (MScEng)--University of Stellenbosch, 2005. / ENGLISH ABSTRACT: This thesis documents the research, design, implementation and successful testing of a prototype camera probe to survey the inside of hard rock boreholes. Rock core images are intended to aid mine geologists in recording the borehole rock layers. The system consists of a wide-angle fisheye lens mounted onto a CMOS digital image sensor. The image data is read in and processed by an FPGA, then stored on a removable sn flash memory card. All of the aforementioned components are mounted inside a watertight Perspex tube. Application specific PC software is used to process the data to form strip images of the borehole wall. Using mathematical correlation, these images are stitched together into a virtual core that is a flattened representation of the rock inside the borehole. The probe contains its own power and light source which enables it to be deployed easily with no external wires needed for operation. The storage capacity, image quality, and lighting design can be improved in future design revisions. / AFRIKAANSE OPSOMMING: Die inhoud van hierdie tesis behels die navorsmg, ontwerp, implementering, en suksesvolle toetsing van 'n prototipe kameraprobe wat dit moontlik maak om die binnewand van boorgate in harde rots te besigtig. Beelde van die rotskern vergemaklik die taak van myngeoloë wat die rotslae, waardeur die boorgat strek, moet opteken. Die stelsel behels 'n wyehoek bollens wat op 'n CMOS digitale sensor gemonteer is. Die data gewerf vir die vorming van die beeld word deur 'n FPGA ingelees en verwerk, waarna dit op 'n verwyderbare SD flits geheuekaart gestoor word. Die bogenoemde komponente word alles binne 'n waterdigte Perspexbuis monteer. Gebruikerspesifieke sagteware vir persoonlik rekenaars word gebruik om die data te verwerk en sodoende strookbeelde van die binnewand van die boorgat te vorm. Met gebruik van wiskundige korrelasie word hierdie beelde aan mekaar gelas om 'n virtuele kern te vorm, wat 'n voorstelling is van die rots binne die boorgat. Die probe bevat self krag en ligbronne, wat toelaat dat dit maklik bruikbaar is sonder enige eksterne bedrading. Toekomstige hersienings van die ontwerp sal verbeterde data geheue, beeldgehalte en beligting kan bewerkstellig.

We describe a framework for global shipping container monitoring using machine learning with multi-sensor hubs and infrared catadioptric imaging. A wireless mesh radio satellite tag architecture provides connectivity anywhere in the world which is a significant improvement to legacy methods. We discuss the design and testing of a low-cost long-wave infrared catadioptric imaging device and multi-sensor hub combination as an intelligent edge computing system that, when equipped with physics-based machine learning algorithms, can interpret the scene inside a shipping container to make efficient use of expensive communications bandwidth. The histogram of oriented gradients and T-channel (HOG+) feature as introduced for human detection on low-resolution infrared catadioptric images is shown to be effective for various mirror shapes designed to give wide volume coverage with controlled distortion. Initial results for through-metal communication with ultrasonic guided waves show promise using the Dynamic Wavelet Fingerprint Technique (DWFT) to identify Lamb waves in a complicated ultrasonic signal.

In this thesis, catadioptric omnidirectional imaging systems are analyzed in detail. Omnidirectional image (ODI) formation characteristics of different camera-mirror configurations are examined and geometrical relations for panoramic and perspective image generation with common mirror types are summarized. A method is developed to determine the unknown parameters of a hyperboloidal-mirrored system using the world coordinates of a set of points and their corresponding image points on the ODI. A linear relation between the parameters of the hyperboloidal mirror is determined as well. Conducted research and findings are instrumental for calibration of such imaging systems. The resolution problem due to the up-sampling while transferring the pixels from ODI to the panoramic image is defined. Enhancing effects of standard interpolation methods on the panoramic images are analyzed and edge detection-based techniques are developed for improving the resolutional quality of the panoramic images. Also, the projection surface alternatives of generating panoramic images are evaluated.

L'objectif principal de cette thèse est de développer des algorithmes génériques d'estimation du mouvement et de la structure à partir d'images de scènes prises par différents types de systèmes d'acquisition centrale : caméra perspective,fish-eye et systèmes catadioptriques, notamment. En supposant que la correspondance entre les pixels de l'image et les lignes de vue dans l'espace est connue, nous travaillons sur des images sphériques, plutôt que sur des images planes (projection des images sur la sphère unitaire), ce qui nous permet de considérer des points sur une vue mieux adaptée aux images omnidirectionnelles et d'utiliser un modèle générique valable pour tous les capteurs centraux. Dans la première partie de cette thèse, nous développons une approche générique de mise en correspondance simple de lignes à partir d'images de scènes urbaines ou péri-urbaines sous la contrainte d'un faible déplacement du capteur,ainsi qu'une contrainte rapide et originale pour apparier des lignes d'un environnement plan par morceaux, indépendante du mouvement de la caméra centrale. Ensuite, nous introduisons une méthode unique et effcace pour estimer le recouvrement entre deux segments sur des images perspectives, diminuant considérablement le temps global de calcul par rapport aux algorithmes connus.Enfin, dans la dernière partie de cette thèse, nous développons un algorithme d'estimation du mouvement et de reconstruction de surfaces pour les scènes planes par morceaux applicable à toutes sortes d'images centrales, à partir de deux vues uniquement et ne nécessitant qu'un nombre minime de correspondances de ligne. Pour démontrer les performances de ces algorithmes, nous les avons expérimentés avec diverses images réelles acquises à partir d'une caméra perspective,une lentille fish-eye, et deux différents types de capteurs paracatadioptriques(l'un est composé d'un miroir simple, et l'autre d'un miroir double). / The primary goal of this thesis is to develop generic motion and structure algorithms for images taken from constructed scenes by various types of central imaging systems including perspective, fish-eye and catadioptric systems. As-suming that the mapping between the image pixels and their 3D rays in space is known, instead of image planes, we work on image spheres (projection of the images on a unit sphere) which enable us to present points over the entire viewsphere suitable for presenting omnidirectional images. In the first part of this thesis, we develop a generic and simple line matching approach for images taken from constructed scenes under a short baseline motion as well as a fast and original geometric constraint for matching lines in planar constructed scenes insensible to the motion of the camera for all types of centralimages including omnidirectional images.Next, we introduce a unique and efficient way of computing overlap between two segments on perspective images which considerably decreases the over all computational time of a segment-based motion estimation and reconstruction algorithm. Finally in last part of this thesis, we develop a simple motion estima-tion and surface reconstruction algorithm for piecewise planar scenes applicable to all kinds of central images which uses only two images and is based on mini-mum line correspondences.To demonstrate the performance of these algorithms we experiment withvarious real images taken by a simple perspective camera, a fish-eye lens, and two different kinds of paracatadioptric sensors, the first one is a folded catadioptric camera and the second one is a classic paracatadioptric system composed of a parabolic mirror in front of a telecentric lens.

In this thesis, a pipeline for structure-from-motion with mixed camera types is described and methods for the steps of this pipeline to make it effective and automatic are proposed. These steps can be summarized as calibration, feature point matching, epipolar geometry and pose estimation, triangulation and bundle adjustment. We worked with catadioptric omnidirectional and perspective cameras and employed the sphere camera model, which encompasses single-viewpoint catadioptric systems as well as perspective cameras. For calibration of the sphere camera model, a new technique that has the advantage of linear and automatic parameter initialization is proposed. The projection of 3D points on a catadioptric image is represented linearly with a 6x10 projection matrix using lifted coordinates. This projection matrix is computed with an adequate number of 3D-2D correspondences and decomposed to obtain intrinsic and extrinsic parameters. Then, a non-linear optimization is performed to refine the parameters. For feature point matching between hybrid camera images, scale invariant feature transform (SIFT) is employed and a method is proposed to improve the SIFT matching output. With the proposed approach, omnidirectional-perspective matching performance significantly increases to enable automatic point matching. In addition, the use of virtual camera plane (VCP) images is evaluated, which are perspective images produced by unwarping the corresponding region in the omnidirectional image. The hybrid epipolar geometry is estimated using random sample consensus (RANSAC) and alternatives of pose estimation methods are evaluated. A weighting strategy for iterative linear triangulation which improves the structure estimation accuracy is proposed. Finally, multi-view structure-from-motion (SfM) is performed by employing the approach of adding views to the structure one by one. To refine the structure estimated with multiple views, sparse bundle adjustment method is employed with a modification to use the sphere camera model. Experiments on simulated and real images for the proposed approaches are conducted. Also, the results of hybrid multi-view SfM with real images are demonstrated, emphasizing the cases where it is advantageous to use omnidirectional cameras with perspective cameras.