STEREO MATCHING IN THE PRESENCE OF NARROW OCCLUDING OBJECTS USING DYNAMIC DISPARITY SEARCH

Most contemporary stereo correspondence algorithms impose global consistency among candidate match-points using Spatial Hierarchy Mechanism- (SHM) based techniques that rely on either the local support within a 2D neighborhood in the image plane and/or cooperative processes between multiple levels of a pixel-resolution or structural-description hierarchy. We analyze the stereo matching failures in SHM-based techniques in the presence of narrow occluding objects and propose the Dynamic Disparity Search (DDS) framework to reduce false-positive matches. Experiments with indoor and outdoor scenes demonstrate a significant reduction in the false-positive match rates of a DDS-based stereo algorithm as compared to those of two existing algorithms.