Performance evaluation of feature detection and matching in stereo visual odometry

In this paper, we try to evaluate which detector and descriptor may be the most appropriate solution in stereo visual odometry and whether there is any bias on calculation methods in visual odometry applications. We summarize the state of art feature detectors and descriptors in visual odometry field and divide them based on their implemented details. We present three new evaluation criterions (Detection Chain Repeatability, Average Detection Chain Re-projection Error and Matching Chain Precision) of feature detectors and descriptors. We also design experiments to evaluate the performance of different detectors and descriptors from the robustness, precision and cost of computation.