Objects tracking in catadioptric images using spherical snake

The current work addresses the problem of 3D model tracking in the context of omnidirectional vision in order to object tracking. However, there is few articles dealing this problem in catadioptric vision. This paper is an attempt to describe a new approach of omnidirectional images (gray level) processing based on inverse stereographic projection in the half-sphere. We used the spherical model. For object tracking, The object tracking method used is snake, with optimization using the Greedy algorithm, by adapting its different operators. This method algorithm will respect the deformed geometry of omnidirectional images such as the spherical neighbourhood, the spherical gradient and reformulation of optimization algorithm on the spherical domain. This tracking method - that we call spherical snake - permit to know the change of the shape and the size of 2D object in different replacements in the spherical image.