Double compression detection based on local motion vector field analysis in static-background videos |
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| Affiliation: | 1. School of Electrical Engineering, Korea University, Seoul, Republic of Korea;2. Department of Electronics Engineering, Ewha Womans University, Seoul 120-750, Republic of Korea;1. Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan;2. Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia;1. Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi, Jiangsu 214122, PR China;2. School of Mechanical Engineering, Jiangnan University, Wuxi, Jiangsu 214122, PR China;1. School of Mathematics and Statistics, Beijing Institute of Technology, Beijing 100081, China;2. Beijing Key Laboratory on MCAACI, Beijing Institute of Technology, Beijing 100081, China;3. Beijing College Finance and Commerce, Beijing 110000, China;1. School of Information Engineering, Guangdong University of Technology, PR China;2. College of Information Science and Engineering, Fujian University of Technology, PR China;3. Harbin Institute of Technology, Shenzhen Graduate School, PR China |
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| Abstract: | Videos captured by stationary cameras are widely used in video surveillance and video conference. This kind of video often has static or gradually changed background. By analyzing the properties of static-background videos, this work presents a novel approach to detect double MPEG-4 compression based on local motion vector field analysis in static-background videos. For a given suspicious video, the local motion vector field is used to segment background regions in each frame. According to the segmentation of backgrounds and the motion strength of foregrounds, the modified prediction residual sequence is calculated, which retains robust fingerprints of double compression. After post-processing, the detection and GOP estimation results are obtained by applying the temporal periodic analysis method to the final feature sequence. Experimental results have demonstrated better robustness and efficiency of the proposed method in comparison to several state-of-the-art methods. Besides, the proposed method is more robust to various rate control modes. |
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| Keywords: | Video forensics Static-background videos Double MPEG-4 compression Background segmentation Local motion vector field Periodic analysis GOP estimation Bit-rate control mode |
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