Moving Object Detection and Tracking in Outside Environments
Background subtraction is a typical method for moving objects detection. The Gaussian mixture model is one of widely used method to model the background. However, in challenge environments, quick lighting changes, noises and shake of background can influence the detection of moving objects significantly. To solve this problem, an improved Gaussian Mixture Model is proposed in this paper. In the proposed algorithm, Objects are divided into three categories, foreground, background and middle-ground. The proposed algorithm is a segmented process. Moving objects including foreground and middle-ground are extracted firstly; then foreground is segmented from middle-ground. In this way almost middle-ground are filtered, so we can obtain a clear foreground objects. Experimental results show that the proposed algorithm can detect moving objects much more precisely, and it is robust to lighting changes and shadows.
Gaussian Mixture Model moving-objects detection lighting variation
Yiding Wang Daqian Li
North China University of Technology, Beijing, China
国际会议
合肥
英文
3862-3865
2011-09-23（万方平台首次上网日期，不代表论文的发表时间）