A voting strategy for visual ego-motion from stereo

We present a procedure for egomotion estimation from visual input of a stereo pair of video cameras. The 3D egomotion problem, which has six degrees of freedom in general, is simplified to four dimensions and further decomposed to two two-dimensional subproblems. The decomposition allows us to use a voting strategy to identify the most probable solution, avoiding the random sampling (RANSAC) or other approximation techniques. The input constitutes of image correspondences between consecutive stereo pairs, i.e. feature points do not need to be tracked over time. The experiments show that even if a trajectory is put together as a simple concatenation of frame-to-frame increments, it comes out reliable and precise.