Conventional cameras are usually small in their field of view (FOV) and make the observable region limited. Applications by such a vision system may also limit motion capabilities for robots when it comes to object tracking. Omnidirectional camera has a wide FOV which can obtain environmental data from all directions. In comparison with conventional cameras, the wide FOV of omnidirectional cameras reduces blind regions and improves tracking ability. In this thesis, we assume an omnidirectional camera is mounted on a moving platform, which travels with planar motion. By applying optical flow and CAMShift algorithm to track an object which is non-propelled and only subjected to gravity. Then, by parabolic fitting, least-square method and Levenberg-Marquardt method to predict the 3D coordinate of the object at the current instant and the next instant, we can finally predict the position of the drop point and drive the moving platform to meet the object at the drop point. The tracking operation and drop point prediction can be successfully achieved even if the camera is under planar motion and rotation.

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.

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.