Contribution to the tracking and the 3D reconstruction of scenes composed of torus from image sequences a acquired by a moving camera

The three-dimensional perception of the environment is often necessary for a robot to correctly perform its tasks. One solution, based on the dynamic vision, consists in analysing time-varying monocular images to estimate the spatial geometry of the scene. This thesis deals with the reconstruction of torus by dynamic vision. Though this object class is restrictive, it enables to tackle the problem of reconstruction of bent pipes usually encountered in industrial environments. The proposed method is based on the evolution of apparent contours of objects in the sequence. Using the expression of torus limb boundaries, it is possible to recursively estimate the object three-dimensional parameters by minimising the error between the predicted projected contours and the image contours. This process, which is performed by a Kalman filter, does not need a precise knowledge of the camera displacement or any matching of the tow limbs belonging to the same object. To complete this work, temporal tracking of objects which deals with occlusion situations is proposed. The approach consists in modeling and interpreting the apparent motion of objects in the successive images. The motion interpretation, based on a simplified representation of the scene, allows to recover pertinent three-dimensional information which is used to manage occlusion situations. Experiments, on synthetic and real images, proves he validity of the tracking and the reconstruction processes. (author)