Browsing by Author "Guo, Ge"

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    Enhanced Gaussian background modeling algorithm and implementation in FPGA for real-time moving object detection in surveillance video
    (University of New Brunswick, 2014) Guo, Ge; Zhang, Yun; Kaye, Mary
    A real-time solution of moving object detection (MOD) in surveillance video was explored in this work motivated by the practical ileed of real-time automated video analysis system. The core element of a moving object detection process is its background modeling algorithm in the content of surveillance and road monitoring applications. By reviewing and analyzing previous works, single Gaussian (SG) background modeling algorithm was selected and enhanced. Then a circuit that performs MOD with enhanced SG algorithm was designed and implemented in a Virtex6 FPGA of a ML605 evaluation board with other hardware components. The experiment results showed that the proposed MOD system could perform real-time MOD in a video of 1280x720p@30fps. It outperforms the software experiments/implementations and the state-of-art FPGA-based implementations.
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    Enhanced Gaussian background modelling algorithm and implementation in FPGA for real-time moving object detection in surveillance video
    Guo, Ge
    A real-time solution of moving object detection (MOD) in surveillance video was explored in this work motivated by the practical need of real-time automated video analysis system. The core element of a moving object detection process is its background modeling algorithm in the content of surveillance and road monitoring applications. By reviewing and analyzing previous works, single Gaussian (SG) background modeling algorithm was selected and enhanced. Then a circuit that performs MOD with enhanced SG algorithm was designed and implemented in a Virtex6 FPGA of a ML605 evaluation board with other hardware components. The experiment results showed that the proposed MOD system could perform real-time MOD in a video of 1280×720p@30fps. It outperforms the software experiments/implementations and the state-of-art FPGA-based implementations.
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    Enhanced Gaussian background modelling algorithm and implementation in FPGA for real-time moving object detection in surveillance video
    Guo, Ge
    A real-time solution of moving object detection (MOD) in surveillance video was explored in this work motivated by the practical need of real-time automated video analysis system. The core element of a moving object detection process is its background modeling algorithm in the content of surveillance and road monitoring applications. By reviewing and analyzing previous works, single Gaussian (SG) background modeling algorithm was selected and enhanced. Then a circuit that performs MOD with enhanced SG algorithm was designed and implemented in a Virtex6 FPGA of a ML605 evaluation board with other hardware components. The experiment results showed that the proposed MOD system could perform real-time MOD in a video of 1280×720p@30fps. It outperforms the software experiments/implementations and the state-of-art FPGA-based implementations.