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.>

Contemporary stereo correspondence algorithms disambiguate multiple candidate matches by using a spatial hierarchy mechanism. Narrow occluding objects in 3-D scenes cannot be handled by the spatial hierarchy mechanism alone. The authors propose a dynamic disparity search (DDS) framework that combines the spatial hierarchy mechanism with a new disparity hierarchy mechanism, to reduce the stereo matching errors caused by narrow occluding objects. They demonstrate the merits of the DDS approach on real stereo images.>

Most contemporary stereo correspondence algorithms impose global consistency among candidate match-points by solely using a spatial hierarchy mechanism. This paper analyzes the stereo matching failures caused by the spatial hierarchy mechanism in the presence of narrow occluding objects. The lessons learned from this occlusion analysis are used to formulate a new global matching framework-dynamic disparity search. The authors present experimental results showing a significant decrease in the false positive match-rate with a dynamic disparity search-based stereo algorithm as compared to a spatial hierarchy mechanism-based algorithm.>

Consideration is given to the twin issues of the gain in accuracy of stereo correspondence and the accompanying increase in computational cost due to the use of a third camera for stereo analysis. The relative performance of binocular and trinocular stereo algorithms on stereo images with known ground truth is evaluated. A technology for comparing the matching performance of stereo algorithms by using real digital elevation maps is developed. Trinocular local matching reduces the percentage of mismatches having large disparity errors by more than one half when compared to binocular matching, while trinocular stereopsis increases the computational cost of local matching over binocular stereopsis by only about one fourth.>

The authors review major recent developments in establishing stereo correspondence for the extraction of the 3D structure of a scene. Broad categories of stereo algorithms are identified on the basis of differences in imaging geometry, matching primitives, and the computational structure used. The performance of these stereo techniques on various classes of test images is reviewed, and possible directions of future research are indicated.>