Globally optimal solution to multi-object tracking with merged measurements

Joao F. Henriques, Rui Caseiro, Jorge Batista
2011 2011 International Conference on Computer Vision  
Multiple object tracking has been formulated recently as a global optimization problem, and solved efficiently with optimal methods such as the Hungarian Algorithm. A severe limitation is the inability to model multiple objects that are merged into a single measurement, and track them as a group, while retaining optimality. This work presents a new graph structure that encodes these multiple-match events as standard one-to-one matches, allowing computation of the solution in polynomial time.
more » ... ce identities are lost when objects merge, an efficient method to identify groups is also presented, as a flow circulation problem. The problem of tracking individual objects across groups is then posed as a standard optimal assignment. Experiments show increased performance on the PETS 2006 and 2009 datasets compared to state-of-the-art algorithms.
doi:10.1109/iccv.2011.6126532 dblp:conf/iccv/HenriquesCB11 fatcat:3azlb3gvsbblbg46ivsgri2v4i