Unified hierarchical multi-object tracking using global data association

This paper presents a unified hierarchical multi-object tracking scheme. The problem of simultaneously tracking multiple objects is cast as a global MAP problem which aims at maximizing the probability of trajectories given the observations in each frame. Directly solving this problem is infeasible, due to computational considerations and the difficulty of reliably estimate necessary transition probabilities. Without breaking the MAP formulation, we propose a three stage hierarchical tracking framework which makes solving the MAP feasible. In addition, using a hierarchical framework allows for modeling inter-object occlusions. Occlusion handling thus smoothly and implicitly integrates into the proposed framework without any explicit occlusion reasoning. Finally, we evaluate the proposed method on the publicly available PETS 2009 tracking data and show improvements over the current state of the art for most sequences.