Omni-directional Multi-baseline Stereo without Similarity Measures

This paper proposes a novel method for estimating depth from long image sequences captured by pre-calibrated moving omni-directional multi-camera system (OMS). Our idea for estimating an omni-directional depth map is very simple; only counting interest points in images is integrated with the framework of conventional multi-baseline stereo. Even by a simple algorithm, depth can be determined without computing similarity measures such as SSD and NCC that have been used for traditional stereo matching. The proposed method realizes robust depth estimation against image distortions and occlusions with lower computational cost than traditional multi-baseline stereo method. These advantages of our method are fit for characteristics of omnidirectional cameras. In experiments, validity and feasibility of our algorithm are shown for both a synthetic and real outdoor scene.