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fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Languages: English
Types: Other
Subjects: QA75
This paper presents an accelerated version of a\ud dense stereo-correspondence algorithm for two different parallelism\ud enabled architectures, multi-core CPU and GPU. The\ud algorithm is part of the vision system developed for a binocular\ud robot-head in the context of the CloPeMa 1 research project.\ud This research project focuses on the conception of a new clothes\ud folding robot with real-time and high resolution requirements\ud for the vision system. The performance analysis shows that\ud the parallelised stereo-matching algorithm has been significantly\ud accelerated, maintaining 12x and 176x speed-up respectively\ud for multi-core CPU and GPU, compared with non-SIMD singlethread\ud CPU. To analyse the origin of the speed-up and gain\ud deeper understanding about the choice of the optimal hardware,\ud the algorithm was broken into key sub-tasks and the performance\ud was tested for four different hardware architectures.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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