Multiple human tracking with dual cost graphs

Visual tracking gives a trajectory of a person’s movement in a video. It is an important element of human’s behavior analysis. However, the performance of the most visual tracking methods does not satisfy precision and speed for use in the real world. High accuracy and low computation complexity are demanded but these two have a relation of trade-off. Therefore, we aim to propose a tracking method that balances accuracy and computational complexity. In this paper, we proposed a method named Dual Cost Graph (DCG)-Tracker using the graphs referred to as a clique graph and a flow network. We evaluated DCG-Tracker with PNNL parking lot 1 dataset1, 2 and showed that it balances between accuracy and speed.