Parallel Background Subtraction in Video Streams using OpenCL on GPU Platforms

  • Grzegorz Szwoch. Parallel Background Subtraction in Video Streams using OpenCL on GPU Platforms. In 18th IEEE Conference SPA 2014: Signal Processing: Algorithms, Architectures, Arrangements, and Applications, pages 54-59, Poznan,Poland, 2014.
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    Implementation of the background subtraction algorithm using OpenCL platform is presented. The algorithm processes live stream of video frames from the surveillance camera in on-line mode. Processing is performed using a host machine and a parallel computing device. The work focuses on optimizing an OpenCL algorithm implementation for GPU devices by taking into account specific features of the GPU architecture, such as memory access, data transfers and work group organization. However, the algorithm is intended to be used on any OpenCL compliant devices, including DSP and FPGA platforms. Various optimizations of the algorithm are presented and tested using a number of devices with varying processing power. The main aim of the work is to determine which optimizations are essential for ensuring on-line video processing in the surveillance system.

    @InProceedings{2014-09-SZWOCH,
    author = {Grzegorz Szwoch},
    title = {{Parallel Background Subtraction in Video Streams using OpenCL on GPU Platforms}},
    booktitle = {{18th IEEE Conference SPA 2014: Signal Processing: Algorithms, Architectures, Arrangements, and Applications}},
    date = {2014-09-22/2014-09-24},
    pages = {54-59},
    address = {Poznan,Poland},
    url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber = 7067270&filter%3DAND(p_IS_Number%3A7067255)},
    abstract = {Implementation of the background subtraction algorithm using OpenCL platform is presented. The algorithm processes live stream of video frames from the surveillance camera in on-line mode. Processing is performed using a host machine and a parallel computing device. The work focuses on optimizing an OpenCL algorithm implementation for GPU devices by taking into account specific features of the GPU architecture, such as memory access, data transfers and work group organization. However, the algorithm is intended to be used on any OpenCL compliant devices, including DSP and FPGA platforms. Various optimizations of the algorithm are presented and tested using a number of devices with varying processing power. The main aim of the work is to determine which optimizations are essential for ensuring on-line video processing in the surveillance system.},
    year = {2014}
    }

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