Absolute Stereo SFM without Stereo Correspondence for Vision Based SLAM

This paper presents a vision based SLAM method by using stereo SFM technique. The proposed method is based on the stereo SFM presented in our former paper. The method do not need stereo correspondence but, nevertheless, can determine absolute scale factor, which is an important factor for long term navigation and SLAM. The method use only motion correspondence basically, which is easier to solve than stereo correspondence because the SFM algorithm can use a sequence of images taken at short time intervals. However, we infer the stereo correspondence inversely from the absolute estimates of structure and motion parameters and utilize this information to improve the performance of our method. Consequently, the method maintain the robustness to the stereo correspondence ambiguity and can avoid the degenerate configuration reported in the former paper. We also propose a simple initialization technique for the proposed method based on extended Kalman filter, which is critical issue for the methods using bearing-only measurements. The experimental results demonstrate the effectiveness of the algorithm.