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Real-time Multi-view Stereo Algorithm using Adaptive-weight Parzen Window and Local Winner-take-all Optimization

This paper presents a real-time multi-view stereo algorithm, which is based on local winner-take-all optimization. When computing the disparity maps for a given view, the algorithm performs 3 steps: cost volume generation, cost volume merging, and disparity selection. The main focus of this paper is on the second step and a new cost volume merging method is proposed, which combines the adaptive weight and the Parzen window approaches. The proposed method can deal with noise and visibility problems effectively, even with poorly generated cost volumes as input. The experimental results demonstrate the validity of our presented approach.