Handling occlusion in object tracking in stereoscopic video sequences

In this paper, we study simple algorithms for three-dimensional tracking objects in a stereo video sequence, by combining optical flow and stereo vision. This method is not able to handle the occlusion of the moving objects when they disappear due to an obstacle. To improve the performance of this method, we propose the use of adaptive filters and neural networks to predict the expected instantaneous velocities of the objects. In the previous works, this system has been successfully proved in two-dimensional tracking.