3D Label Optimization Based on Triangulation and Superpixel Structures

The algorithm based on a 3D label can obtain a more accurate sub-pixel disparity map in the stereo matching problem. To overcome the random initialization of 3D labels, we proposed a label initialization approach based on superpixel structure and triangulation. An initial 3D label is generated by triangulating the feature points retrieved from the superpixel boundary. To increase the efficiency of the graph cut approach in iterative optimization of 3D labels, we conduct optimization on the superpixel structure, adding the hypothesis of current label state throughout the iteration to expand the label candidates, which improves label search efficiency. Experiments on the Middlebury2014 dataset demonstrate that the proposed approach has a lower average error rate (8. 31%) than the LocalExp algorithm (8. 39%), and the average processing time for single image is similar to 70% that of the LocalExp algorithm.