Spatiotemporal 3D motion vector filtering method for robust visual odometry

Most of the previous visual odometry methods cannot deal with a large independently moving object that takes up over 50% of the image area. To overcome this problem, the spatiotemporal filter is incorporated into the RANSAC method to filter out false match that occurrs by a large independently moving object. This spatiotemporal filter uses the current and previous motion vector%s length and direction. Experimental results demonstrate that the proposed method effectively rejects the motion vectors generated from large independently moving objects and improves the visual odometry accuracy.