期刊
IEEE TRANSACTIONS ON CYBERNETICS
卷 49, 期 6, 页码 1990-2001出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCYB.2018.2803217
关键词
Low-level tracklet; multiobject tracking (MOT); submodular optimization; tracklets selecting process
类别
资金
- Beijing Natural Science Foundation [4182056]
- National Basic Research Program of China (973 Program) [2013CB328805]
- National Natural Science Foundation of China [61272359, 61379087, 61602183]
- UGC Direct Grant for Research [4055060]
- Australian Research Council [FL-170100117, DP-140102164, LP-150100671]
- Fok Ying Tung Education Foundation [141067]
- Specialized Fund for Joint Building Program of Beijing Municipal Education Commission
In this paper, we propose a new multiobject visual tracking algorithm by submodular optimization. The proposed algorithm is composed of two main stages. At the first stage, a new selecting strategy of tracklets is proposed to cope with occlusion problem. We generate low-level tracklets using overlap criteria and man-cost How, respectively, and then integrate them into a candidate tracklets set. In the second stage, we formulate the multiobject tracking problem as the submodular maximization problem subject to related constraints. The submodular function selects the correct tracklets from the candidate set of tracklets to form the object trajectory. Then, we design a connecting process which connects the corresponding trajectories to overcome the occlusion problem. Experimental results demonstrate the effectiveness of our tracking algorithm.
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