  In this paper, a new network-transmission-based (NTB) algorithm is proposed
for human activity recognition in videos. The proposed NTB algorithm models the
entire scene as an error-free network. In this network, each node corresponds
to a patch of the scene and each edge represents the activity correlation
between the corresponding patches. Based on this network, we further model
people in the scene as packages while human activities can be modeled as the
process of package transmission in the network. By analyzing these specific
"package transmission" processes, various activities can be effectively
detected. The implementation of our NTB algorithm into abnormal activity
detection and group activity recognition are described in detail in the paper.
Experimental results demonstrate the effectiveness of our proposed algorithm.
