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| Moving Object Detection Optimization Algorithm Based on Robust Principal Component Analysis |
| YANG Yizhong WANG Pengfei HU Xionglou WU Nengju |
| (School of Electronic Science & Applied Physics, Hefei University of Technology, Hefei 230009, China) |
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Abstract Since dynamic background may be erroneously detected as a moving object in the Robust Principal Component Analysis (RPCA) algorithm, a RPCA-based moving object detection optimization algorithm is proposed to improve it. After detected by the RPCA algorithm, the moving object will be separated from dynamic background according to the Gaussian distribution of dynamic background in the time domain and the difference of mean value and variance between dynamic background and moving object in the whole video stream. The results show that the algorithm can deal with dynamic background effectively and detect the moving objects well.
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Received: 04 August 2017
Published: 14 March 2018
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| Fund:The National Natural Science Foundation of China (61401137, 61404043), The Key Science and Technology Project of Anhui Province (16030901007), The Fundamental Research Funds for the Central Universities (J2014HGXJ0083) |
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Corresponding Authors:
YANG Yizhong
E-mail: yangyizhong@hfut.edu.cn
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