2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) 2018
DOI: 10.1109/atsip.2018.8364449
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Efficient parallelization of GMM background subtraction algorithm on a multi-core platform for moving objects detection

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Cited by 6 publications
(1 citation statement)
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“…The third approach is based on using parallel computing under di↵erent architectures. On multi-core architecture, the authors of [7] proposed a parallel implementation for GMM using the OpenMP framework. On GPU architecture, there are many implementations to parallelize BS using di↵erent optimization techniques (such as memory coalescing, data transfer, kernel overlapping, divergent branch elimination, and e cient register usage) [8][9][10].…”
mentioning
confidence: 99%
“…The third approach is based on using parallel computing under di↵erent architectures. On multi-core architecture, the authors of [7] proposed a parallel implementation for GMM using the OpenMP framework. On GPU architecture, there are many implementations to parallelize BS using di↵erent optimization techniques (such as memory coalescing, data transfer, kernel overlapping, divergent branch elimination, and e cient register usage) [8][9][10].…”
mentioning
confidence: 99%