Fast Adaptive Graph-Cuts Based Stereo Matching

Stereo vision is one of the central research problems in computer vision. The most difficult and important issue in this area is the stereo matching process. One technique that performs this process is the Graph-Cuts based algorithm and which provides accurate results [1]. Nevertheless, this approach is too slow to use due to the redundant computations that it invokes. In this work, an Adaptive Graph-Cuts based algorithm is implemented. The key issue is to subdivide the image into several regions using quadtrees and then define a global energy function that adapts itself for each of these subregions. Results show that the proposed algorithm is 3 times faster than the other Graph-Cuts algorithm while keeping the same quality of the results.