3D cost aggregation with multiple minimum spanning trees for stereo matching.

Cost aggregation is one of the key steps in the stereo matching problem. In order to improve aggregation accuracy, we propose a cost-aggregation method that can embed minimum spanning tree (MST)-based support region filtering into PatchMatch 3D label search rather than aggregating on fixed size patches. However, directly combining PatchMatch label search and MST filtering is not straightforward, due to the extremely high complexity. Thus, we develop multiple MST structures for cost aggregation on plenty of 3D labels, and design the tree-level random search strategy to find possible 3D labels of each pixel. Extensive experiments show that our method reaches higher accuracy than the other existing cost-aggregation and global-optimization methods such as the 1D MST, the PatchMatch and the PatchMatch Filter, and currently ranks first on the Middlebury 3.0 benchmark.