Structural Constraint Data Association for Online Multi-object Tracking

Author:

Yoon Ju HongORCID,Lee Chang-Ryeol,Yang Ming-Hsuan,Yoon Kuk-Jin

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Reference45 articles.

1. Bae, S. H., Yoon, K. J. (2014). Robust online multi-object tracking based on tracklet confidence and online discriminative appearance learning. InProceedings of IEEE conference on computer vision and pattern recognition (pp. 1218–1225).

2. Bar-Shalom, Y., & Li, X. R. (1995). Multitarget-multisensor tracking: Principles and techniques. Storrs, CT: YBS Publishing.

3. Bernardin, K., & Stiefelhagen, R. (2008). Evaluating multiple object tracking performance: The clear mot metrics. EURASIP Journal on Image and Video Processing, 1(1–1), 10.

4. Betke, M., & Wu, Z. (2016). Data Association for multi-object visual tracking. Synthesis lectures on computer vision. Morgan & Claypool. https://books.google.co.kr/books?id=tn0cvgAACAAJ .

5. Blackman, S., & Popoli, R. (1999). Design and analysis of modern tracking systems. Norwood: Artech House Radar Library, Artech House.

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