Background Modeling and Moving Object Detection Based on YC_bC_r Color Space
Lang Su-juan · Journal of Nanjing University of Posts and Telecommunications · 2009
Gaussians mixture model (GMM) has been widely used for moving object detection based on background modeling.In this paper,the background is firstly modeled using adaptive Gaussian mixture models in YCbCr color space,and the foreground regions including moving objects and cast shadow are extracted from current frame by comparing the each pixel with Gaussian model.Then,the texture of little patches is represented by local binary patterns and the cast shadow is detected and eliminated based on the texture similarity between shadow region and corresponding region in the background.Finally,the geometric features of cast shadow are imposed to further improve the performance of moving object detection.Experimental results demonstrate the proposed algorithm can effectively detect cast shadow and moving object,and has higher practicability.