Enhancing the association in multi‐object tracking via neighbor graph-Reference-Cited by-同舟云学术

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Enhancing the association in multi‐object tracking via neighbor graph

Published:2021-07-26 Issue:11 Volume:36 Page:6713-6730
ISSN:0884-8173
Container-title:International Journal of Intelligent Systems
language:en
Short-container-title:Int J Intell Syst

Author:

Liang Tianyi¹²^ORCID,Lan Long³^ORCID,Zhang Xiang³^ORCID,Peng Xindong¹^ORCID,Luo Zhigang⁴^ORCID

Affiliation:

1. College of Computer National University of Defense Technology Changsha China

2. Shandong Sport University Jinan China

3. Institute for Quantum Information & State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China

4. Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China

Publisher

Wiley

Subject

Artificial Intelligence,Human-Computer Interaction,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/int.22565

Reference45 articles.

1. A benchmark for clothes variation in person re‐identification

2. ZengK NingM WangY GuoY. Hierarchical clustering with hard‐batch triplet loss for person re‐identification. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. Piscataway NJ: IEEE;2020:13657‐13665.

3. Leal‐TaixeL Pons‐MollG RosenhahnB. Everybody needs somebody: modeling social and grouping behavior on a linear programming multiple people tracker. In:2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops). Piscataway NJ: IEEE;2011:120‐127.

4. DuanG AiH CaoS LaoS. Group tracking: exploring mutual relations for multiple object tracking. In:Proceedings of the 12th European Conference on Computer Vision (ECCV '12). Vol III. Berlin Heidelberg: Springer;2012:129‐143.

5. LuberM StorkJA TipaldiGD ArrasKO. People tracking with human motion predictions from social forces. In:2010 IEEE International Conference on Robotics and Automation. Piscataway NJ: IEEE;2010:464‐469.

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4. Aerial Multi-object Tracking via Information Weighting;Lecture Notes in Computer Science;2024

5. DSGA: Distractor-Suppressing Graph Attention for Multi-object Tracking;Proceedings of the 8th International Conference on Robotics and Artificial Intelligence;2022-11-18

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