Real-Time Stereo Matching using Adaptive Window based Disparity Refinement

Zheng Tian, Cheng Xu, Xin Huang, Xiaodong Wang
Hunan University, College of Information Science and Engineering, 2 Lushan South Road, Yuelu District, Changsha, China, 410082
International Conference on Multimedia and Human Computer Interaction (MHCI), 2013

   title={Real-Time Stereo Matching using Adaptive Window based Disparity Refinement},

   author={Tian, Zheng and Xu, Cheng and Huang, Xin and Wang, Xiaodong},



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In this paper, we propose a real-time stereo matching method based on adaptive window, aiming at the trade-off between accuracy and efficiency in current local stereo matching, Considering that the Census transform has good adaptability to image amplitude distortion, but may introduce matching ambiguities in regions with noise or similar local structures, we combine the Census transform with AD (absolute differences) for matching cost initialization, and adopt an iterative cost aggregation method based on ESAW (exponential step adaptive weight), in order to improve the parallelism and execution efficiency. Furthermore, in disparity refinement stage, we build adaptive window based on pixel’s color similarity and Euclidean distance for each unreliable point. and classify the unreliable points as "occlusion" and "mismatch", so different refinement strategies could be taken for different classifications. Finally the proposed method is optimized with CUDA (compute unified device architecture) and evaluated on graphic processor. The experiment results show that the proposed method is the most accurate one compared with real-time stereo matching methods listed on the Middlebury stereo benchmark.
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