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Conference papers
Optimized Belief Propagation Algorithm onto Embedded Multi and Many-Core Systems for Stereo Matching
Abstract : Stereo matching techniques aim at reconstructing disparity maps from a pair of images. The use of stereo matching techniques in embedded systems is very challenging due to the complexity of the state-of-the-art algorithms. Local stereo matching algorithms are efficiently implemented on GPU and DSP. This paper presents the optimization of the One Dimension Belief Propagation (BP-1D) algorithm. BP-1D is faster than previous algorithms on monocore DSP and its implementation onto multicore DSPs is straightforward. BP-1D implemented on multicore embedded platforms out-performs previous stereo matching implementations reaching real-time performances for resolutions up to 1080p with a 10 Watts power consumption. © 2016 IEEE.
Keywords :
Local stereo matching
Multi-core dsp
Real time performance
State-of-the-art algorithms
Stereo matching
Vision processing
Stereo image processing
Embedded visions
Belief propagation algorithm
Stereo vision
Optimization
Image matching
Embedded systems
Complex networks
Algorithms
Backpropagation
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01368103
Contributor : Laurent Jonchère <>
Submitted on : Monday, September 19, 2016 - 10:21:40 AM
Last modification on : Monday, October 5, 2020 - 9:50:24 AM
Contributor : Laurent Jonchère <>
Submitted on : Monday, September 19, 2016 - 10:21:40 AM
Last modification on : Monday, October 5, 2020 - 9:50:24 AM