Abstract:

A feedback model was put forward in order to improve the realtime capability of intelligent video surveillance. First, the background subtraction method based on Gaussian mixture model was adopted to detect moving objects. And the Kalman filter algorithm was adopted to perform the realtime object tracking. Then a feedback model was put forward. In the model, the results of tracking was fed back to the detection stage in order to restrict the detection regions. By experiments, the proposed method(which used the feedback model) was compared with the common method(which didn′t use the feedback model). The experimental results illustrate the good performance and enhanced realtime capability of the proposed method.

Key words: computer application, intelligent video surveillance, moving object detection, object tracking, Gaussian mixture model, Kalman fiter