An efficient low cost background subtraction method to extract foreground object during human tracking

Moving object detection in video streams is the fundamental and relevant step in many computer vision applications such as video surveillance for people tracking. Background subtraction is a widely used approach for detecting moving objects in videos from static cameras. This paper describes an efficient background subtraction technique for extracting the moving objects from a scene. Gaussian mixture models (GMM) gives best results than other segmentation methods.