A new network-based algorithm for multi-camera abnormal activity detection

In this paper, a new abnormal activity detection algorithm is proposed for multi-camera surveillance applications. The proposed algorithm models the entire scene covered by the multi-camera system as a network. In this network, each node corresponds to a segmentation of the entire scene and each edge represents the activity correlation between the corresponding segmentations. Based on this network, the proposed algorithm further models human activities as the signal transmission process in the network. Thus, abnormal activities can be detected if their ´network transmission energy´ is obviously larger than the normal case. Compared with the previous methods, the proposed algorithm is more general and is flexible to handle various multi-camera scenarios and configurations. Experimental results demonstrate the effectiveness of the proposed algorithm.