Edge points-based stereo matching approach for omnidirectional images

We address the problem of matching stereo-omnidirectional images acquired by a catadioptric stereo system. The proposed approach deals with omnidirectional stereo image sequences, which allows taking advantage of the temporal information in both rectification and stereo matching steps. First, spherical edge points detection is performed on the spherical images in order to compute the disparity map only on significant features, i.e., edge points. Second, a spherical rectification is performed on the three omnidirectional pairs that are involved in the disparity map computation at the current frame, such as the current pair, the current left image, and its preceding one, and the current right image and its preceding one. Third, dynamic programming-based stereo matching is applied in each of the three stereo pairs. The disparity maps computed at the preceding frame are exploited to deduce the disparity range that will be used by the dynamic programming. Fourth, the three disparity maps provided by the last step are combined together into one 360-deg disparity map. The proposed method has been tested on a high-resolution omnidirectional images captured with a stereo pair of catadioptric cameras, and the obtained results are satisfactory. (C) 2018 SPIE and IS&T.