Exploitation de contraintes photométriques et géométriques en vision : application au suivi, au calibrage et à la reconstruction
The topic of this thesis revolves around three fundamental problems in computer vision; namely, video tracking, camera calibration and shape recovery. The proposed methods are solely based on photometric and geometric constraints found in the images. Video tracking, usually performed on a video sequence, consists in tracking a region of interest, selected manually by an operator. We extend a successful tracking method by adding the ability to estimate the orientation of the tracked object. Furthermore, we consider another fundamental problem in computer vision: cali- bration. Here we tackle the problem of calibrating linear cameras (a.k.a: pushbroom) and video projectors. For the former one we propose a convenient plane-based cali- bration algorithm and for the latter, a calibration algorithm that does not require a physical grid and a planar auto-calibration algorithm. Finally, we pointed our third research direction toward shape reconstruction using coplanar shadows. This technique is known to suffer from a bas-relief ambiguity if no extra information on the scene or light source is provided. We propose a simple method to reduce this ambiguity from four to a single parameter. We achieve this by taking into account the visibility of the light spots in the camera.
Vision 3D Computer vision 3D reconstruction Pushbroom camera Shape-From-Shadow Video tracking Calibration Auto-calibrage plan Planar auto-calibration Projector-Camera system