Moving Objects Detection and Shadows Elimination for Video Sequence

A novel illumination-invariant Cauchy distribution based change detection using shading model(SM) for a fixed visual surveillance system is proposed.Both the initialization method of Gaussian background models and the estimation of parameters for the Cauchy distribution model under the maximum likelihood estimation are presented.Based on results of change detection using statistical hypothesis test,the intensity,hue and saturation in the YCbCr color space are employed to recognize and eliminate shadows and reflections in video sequences.Finally,experimental results demonstrate that the proposed method of background modeling can tolerate changes in illumination,and noises caused by some small motions,shadows or reflections in a background scene.The proposed approach also improves the performance of objects detection in darker regions.