Video Segmentation Algorithm with Gaussian Mixture Model and Shadow Removal
Jinwen Tian · Guangdian gongcheng · 2008
Background subtraction based on Gaussian Mixture Model (GMM) is a common method for real-time video segmentation of moving objects. An effective adaptive background updating method based on GMM is presented. The number of mixture components of GMM is estimated according to the frequency of pixel value changes,and the performance of GMM can be effectively improved with the modified background learning and update new distribution generation rule and shadow removal based on morphological reconstruction. The detection of sudden illumination change and background updating are also proposed. Compared with existing approaches,experimental results with different real scenes demonstrate the robustness of the proposed method.