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  • Open Access


    Moving Object Detection and Tracking Algorithm Using Hybrid Decomposition Parallel Processing

    M. Gomathy Nayagam1,*, K. Ramar2, K. Venkatesh3, S. P. Raja4

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1485-1499, 2022, DOI:10.32604/iasc.2022.023953

    Abstract Moving object detection, classification and tracking are more crucial and challenging task in most of the computer vision and machine vision applications such as robot navigation, human behavior analysis, traffic flow analysis and etc. However, most of object detection and tracking algorithms are not suitable for real time processing and causes slower processing speed due to the processing and analyzing of high resolution video from high-end multiple cameras. It requires more computation and storage. To address the aforementioned problem, this paper proposes a way of parallel processing of temporal frame differencing algorithm for object detection and contour tracking using the… More >

  • Open Access


    Surveillance Video Key Frame Extraction Based on Center Offset

    Yunzuo Zhang1,*, Shasha Zhang1, Yi Li1, Jiayu Zhang1, Zhaoquan Cai2, Shui Lam3

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 4175-4190, 2021, DOI:10.32604/cmc.2021.017011

    Abstract With the explosive growth of surveillance video data, browsing videos quickly and effectively has become an urgent problem. Video key frame extraction has received widespread attention as an effective solution. However, accurately capturing the local motion state changes of moving objects in the video is still challenging in key frame extraction. The target center offset can reflect the change of its motion state. This observation proposed a novel key frame extraction method based on moving objects center offset in this paper. The proposed method utilizes the center offset to obtain the global and local motion state information of moving objects,… More >

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