Multiple people tracking is a challenging task of the computer vision domain, with applications in surveillance, action recognition and for example human-computer interaction systems.
Whereas single object tracking can be considered as almost solved, multiple people tracking still remains a difficult problem with ongoing research, due to the complex interaction between persons, that needs to be modeled in order to obtain good results.
We are interested in finding the global optimal solution to the data association problem. In order to do so, we propose to solve the tracking problem by using knowledge from graph theory:
