Spatio-temporal interaction for aerial video change detection

With the growing capacity of video devices, human operators are nowadays overwhelmed by the huge volumes of data generated in different applications including surveillance. Therefore, automatic video processing techniques are required in order to filter out uninteresting data and to focus the attention of operators. However, reliability is still a challenging problem. In this paper, we show how spatio-temporal redundancy may be exploited to enhance the accuracy of automatic change detection in aerial videos. More precisely, we present an algorithm based on Belief Propagation in order to improve spatio-temporal consistency between successive change detection results. Experiments demonstrate that our method leads to increased accuracy in change detection.