Model-based temporal object verification using video

An approach to model-based dynamic object verification and identification u sing video is proposed. From image sequences containing the moving object, we compute its motion trajectory. Then we estimate its three-dimensional (3 -D) pose at each time step, Pose estimation is formulated as a search probl em, with the search space constrained by the motion trajectory information of the moving object and assumptions about the scene structure. A generaliz ed Hausdorff metric, which is more robust to noise and allows a confidence interpretation, is suggested for the matching procedure used for pose estim ation as well as the identification and verification problem. The pose evol ution curves are used to assist in the acceptance or rejection of an object hypothesis. The models are acquired from real image sequences of the objec ts, Edge maps are extracted and used for matching, Results are presented fo r both infrared and optical sequences containing moving objects involved in complex motions.