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| 论文编号: |
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| 第一作者所在部门: |
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| 中文论文题目: |
Multi-Camera Multi-Target Tracking with Space-Time-View Hyper-graph
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| 英文论文题目: |
Multi-Camera Multi-Target Tracking with Space-Time-View Hyper-graph
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| 论文题目英文: |
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| 作者: |
Wen, Longyin
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| 论文出处: |
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| 刊物名称: |
INTERNATIONAL JOURNAL OF COMPUTER VISION
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| 年: |
2017
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| 卷: |
122 |
| 期: |
2 |
| 页: |
313-333 |
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| 摘要: |
Incorporating multiple cameras is an effective solution to improve the performance and robustness of multi-target tracking to occlusion and appearance ambiguities. In this paper, we propose a new multi-camera multi-target tracking method based on a space-time-view hyper-graph that encodes higher-order constraints (i.e., beyond pairwise relations) on 3D geometry, appearance, motion continuity, and trajectory smoothness among 2D tracklets within and across different camera views. We solve tracking in each single view and reconstruction of tracked trajectories in 3D environment simultaneously by formulating the problem as an efficient search of dense sub-hypergraphs on the space-time-view hyper-graph using a sampling based approach. Experimental results on the PETS 2009 dataset and MOTChallenge 2015 3D benchmark demonstrate that our method performs favorably against the state-of-the-art methods in both single-camera and multi-camera multi-target tracking, while achieving close to real-time running efficiency. We also provide experimental analysis of the influence of various aspects of our method to the final tracking performance. |
| 英文摘要: |
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