Motion Detection with Adaptive Background and Dynamic Thresholds

Human motion detection is a fundamental part for many computer vision tasks and various methods have been proposed. Background subtraction is a very popular method where the classification of pixels into motion pixels and background pixels is based on thresholding the difference image between a background image and a current image. The choice of threshold is crucial and many methods have been employed, from a preset threshold for the whole image to adaptive thresholds for each pixel. In this paper, a motion detection method by dynamically thresholding the difference image is proposed. We keep a static background image that is updated periodically, and compare the incoming frame with it to obtain the absolute difference image. If through a preliminary judgement that there are moving objects in the scene, Otsu´s thresholding method is used to find the threshold to binarize the difference image. Experimental results demonstrate the effectiveness of our method