A self-adaptive optical flow method for the moving object detection in the video sequences |
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Authors: | Yunhong Xin Jie Hou Leming Dong Liping Ding |
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Affiliation: | 1. School of Physics and Information Technology, Shaanxi Normal University, Xi’an 710062, PR China;2. School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi’an 710062, PR China |
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Abstract: | This paper proposes a self-adaptive optical flow method to detect moving objects in the video sequences. The method first estimates the original optical flow field with the optical flow algorithm, and then enhances the objects by a local mean algorithm, and finally filters out the noise with a self-adaptive threshold algorithm. The proposed method has a wide adaptivity to the size and the number of objects, and it also can effectively process the scenarios of complex background and that of the slight occlusion. Furthermore, it avoids the complicated and time-consuming preprocessing procedure. The results of the present method show that the moving objects can be detected effectively. |
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Keywords: | Detection Video sequences Optical flow Local mean Self-adaptive threshold |
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