Moving object detection and tracking from video captured by moving camera |
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| Affiliation: | 1. Department of Computer Science and Information Engineering, National Penghu University of Science and Technology, Penghu, Taiwan, ROC;2. Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan, ROC;3. Department of Electrical Engineering, Dayeh University, Taiwan, ROC;4. Whetron Electronics Co., Ltd, Taiwan, ROC;1. School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an 710049, PR China;2. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210093, PR China;1. School of Computer Science and Technology, Tianjin University, China;2. School of Computer Science & Software Engineering, Shenzhen University, China;3. Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin University, China;4. Department of Mathematics and Computer Science, Hengshui University, China;1. Key Lab of Intelligent Information Processing, Institute of Computing technology, Chinese Academy of Sciences, Beijing 100190, China;2. Institute of Digital Media, Peking University, Beijing 100871, China;3. School of Electronic and Computer Engineering, Peking University Shenzhen Graduate School, Shenzhen 518005, China |
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| Abstract: | This paper presents an effective method for the detection and tracking of multiple moving objects from a video sequence captured by a moving camera without additional sensors. Moving object detection is relatively difficult for video captured by a moving camera, since camera motion and object motion are mixed. In the proposed method, the feature points in the frames are found and then classified as belonging to foreground or background features. Next, moving object regions are obtained using an integration scheme based on foreground feature points and foreground regions, which are obtained using an image difference scheme. Then, a compensation scheme based on the motion history of the continuous motion contours obtained from three consecutive frames is applied to increase the regions of moving objects. Moving objects are detected using a refinement scheme and a minimum bounding box. Finally, moving object tracking is achieved using a Kalman filter based on the center of gravity of a moving object region in the minimum bounding box. Experimental results show that the proposed method has good performance. |
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| Keywords: | Object detection Moving camera Object tracking Feature classification Image difference Object motion Motion history Ego-motion compensation |
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