Comparison of Dense Stereo Using CUDA
In this paper, a local and a global dense stereo matching method, implemented using Compute Unified Device Architecture (CUDA), are presented, analyzed and compared. The purposed work shows the general strategy of the parallelization of matching methods on GPUs and the tradeoff between accuracy and run-time on current GPU hardware. Two representative and widely-used methods, the Sum of Absolute Differences (SAD) method and the Semi-Global Matching (SGM) method, are used and their results are compared using the Middlebury test sets.
KeywordsShared Memory Global Memory Thread Block Epipolar Line Cost Aggregation
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