Caged mice mating behavior detection in surveillance videos |
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| Institution: | 1. Department of Animal Science and Biotechnology, Tunghai University, No. 1727, Section 4, Taiwan Boulevard, Taichung City 40704, Taiwan;2. Department of Electrical Engineering, National Yunlin University of Science and Technology, No. 123, University Road, Section 3, Douliou, Yunlin 64002, Taiwan;1. School of Computer Science, Northwestern Polytechnic University, Xi’an, Shaanxi 710129, PR China;2. School of Electronics and Information, Zhongyuan University of Technology, Zhengzhou, Henan 450007, PR China;3. Department of Computer Science and Information Systems, Birkbeck College, University of London, Bloomsbury, London WC1E 7HX, UK;4. Information Center of Yellow River Conservancy Commission, Zhengzhou, Henan 450003, PR China;1. Department of Electronic Engineering, The Chinese University of Hong Kong, Shatin N.T., Hong Kong;2. Hong Kong Applied Science and Technology Research Institute (ASTRI), Shatin N.T., Hong Kong;1. School of Information Science and Technology, Sun Yat-sen University, Guangzhou 510006, China;2. School of Software, Sun Yat-sen University, Guangzhou 510006, China |
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| Abstract: | The purpose of this study is to develop a computer vision-based method to automatically detect the mating behavior of caged mice in surveillance videos. Previously we took advantage of our developed algorithm and analyzed the objects of mating mice in the consecutive frames, we unprecedentedly showed that, to the best of our knowledge, the mice mating behavior can be automatically detected based on video processing (Lo et al., 2009 13]). In this paper, we proposed an improved method which monitors the distance between two mating objects and more effectively detects the mating behavior. In addition, a more detailed portrayal of the mating behavior can be further elaborated as a function of the distance patterns in the tails of two caged mice. Experimental results show that the current system can effectively detect the mice mating behavior with the highest precision rate of 96.1%, far better than that of our previously proposed method. |
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| Keywords: | Mice mating Animal behavior analysis Video surveillance Caged mice Laboratory animals Tracking techniques Feature extraction Object detection |
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