Fast and robust dense stereo correspondence by column segmentation

The stereo correspondence problem is considered. A new fast and stable algorithm for matching between two rectified images is proposed. The algorithm is based on grouping of image pixels into intervals in image columns and subsequent using dynamic programming technique to produce a dense disparity map. The algorithm enables creating fully automatic - nonparametric stereovision systems. The algorithm can be used in real time stereovision applications, as the sample implementation achieves 15-25fps processing speed in a typical environment. The proposed algorithm enables user to control ratio of speed-quality.