Gestalt Principle Based Change Detection and Background Reconstruction.

Gaussian mixture model based detection algorithms can easily lead to fragmentary due to the fixed number of Gaussian components. In this paper, we propose a gestalt principle based change target extraction method, and further present a background reconstruction algorithm. In particular, firstly we applied the Gaussian mixture model to extract the moving target as others did but this may lead to incomplete extraction. Secondly, we have also tried to apply the frame difference method to extract the moving target more precisely. Finally, we determine to build a static background according to relationships between each frame of a moving target. Experiment results reveal that the proposed detection method outperforms the other three representative detection methods. Moreover, our background reconstruction algorithm is also proved to be very effective and robust in reconstructing the backgrounds of a video.