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Moving Object Detection in Aerial Video
Yunfei Wang; Zhaoxiang Zhang; Yunhong Wang
2012-12-12
会议名称11th International Conference on Machine Learning and Applications
会议录名称ICMLA 2012
会议日期12-15 December 2012
会议地点Boca Raton, Florida, USA
摘要We address the problem of moving object detection in aerial video. Moving object detection in aerial video is still a challenging problem for the reason that when capturing the video the camera (or the platform) is moving all the time. As a result, the problem is detecting moving object from moving background which is much more difficult than the case that the background is constant. To this end, a novel approach is proposed in this paper. Moving object detection in stationary scene usually modeling the pixel value changes over time, but in aerial video the change does not have regular patterns. Therefore, we model the motion of the background rather than modeling the background directly. The optical flow between every two adjacent frames is computed first to get the motion information for each pixel. Based on this, we define a notion named ``pixel motion process" which means the motion changes (the optical flow value changes) of a particular pixel over time, and transfer the Gaussian mixture model framework used for modeling background in the stationary scene to model the background motion. The result is an accurate, adaptive and general background motion model which is used to detect foreground moving objects. Experimental results demonstrate the effectiveness of our approach.
关键词Aerial Video Moving Object Detection Optical Flow Gaussian Mixture Model
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/13255
专题类脑智能研究中心
通讯作者Zhaoxiang Zhang
推荐引用方式
GB/T 7714
Yunfei Wang,Zhaoxiang Zhang,Yunhong Wang. Moving Object Detection in Aerial Video[C],2012.
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