Abstract: Based on edge model, the method of foreground-frame detection with low computational cost was proposed for monitoring the activities of the non-rigid foreground objects in a fixed region. According to the fact that the pixel stability of the foreground edge was far less than that of the background, the steps of the method was as follows: firstly the pseudosphere-based edge detector was used to extract edges in each frame, and the non-background edges were extracted according to the sliding window frames of video sequence (T) and the threshold of judging background edge pixel (η); then the noise edges were eliminated in terms of the threshold of edge pixels; finally the foreground frame was judged according to the threshold of noise edge pixels. Compared with the canny edge detector, in the case of having the same smoothness, pseudosphere-based edge detector offers a lesser error for edge locating. The experimental results on detecting pig in a pigpen showed that the proposed algorithm could effectively adapt to the background in illumination variation and the foreground in slow motion or short stay. This research provides a reference for the subsequence behavior analysis of pigs.