Foreground motion detection by difference-based spatial temporal entropy image

Human motion detection is a fundamental task for many computer vision tasks. The most popular method for motion detection is background subtraction where a background model needs to be maintained. In this paper an entropy based method for human motion detection is described which makes no use of background model. The difference image between consecutive images are calculated and at each particular pixel, and a spatio-temporal histogram is generated by accumulating pixels in difference image. This histogram is then normalized to calculate entropy and the magnitude of entropy is used to denote the significance of motion. Experiment results demonstrate that our method can detect motion object effectively and reliably.