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- W2339424976 abstract "Moving objects detection is important in traffic video analysis, and many algorithms are being increasingly applied to moving objects detection. Most of these algorithms are time-consuming and cannot satisfy real-time demand in traffic video analysis by using a conventional central processing unit (CPU) sequential method. The emergence of the graphics processing unit (GPU) and multi-core CPU provides a method to accelerate the aforementioned algorithms to meet demand. In this study, we provide a GPU-accelerated implementation of the background subtraction algorithm and the morphological operation algorithm. Then, the connected component labeling algorithm is parallelized on a multi-core CPU with Open Multi-Processing (OpenMP). Furthermore, parallel pipeline implementation on a heterogeneous platform is proposed by integrating the aforementioned algorithms. Experimental results show that the proposed implementation achieves a significant speedup of up to 5×, compared with sequential implementation on a CPU." @default.
- W2339424976 created "2016-06-24" @default.
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- W2339424976 date "2015-01-01" @default.
- W2339424976 modified "2023-09-22" @default.
- W2339424976 title "Parallel Pipeline Implementation for Moving Objects Detection in Traffic Video Analysis on a Heterogeneous Platform" @default.
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- W2339424976 doi "https://doi.org/10.1007/978-3-319-11104-9_77" @default.
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