Real-time object tracking without feature extraction

In this paper we propose an appearance-based tracking method without any feature extraction from the images. At first, range-finder system or stereo cameras measure the shape of the incoming object to prepare a CG model of the object. Then many images are generated from the model and compared with input images captured by the cameras. Motion parameter of the object is modified to minimize the difference between generated and captured images, and the parameter tracks the motion of the real object precisely when minimization is converged. At the image generating stage, occlusion is also simulated and we can easily handle the visible region of the object.