Multi-Object Tracking and Segmentation With Embedding Mask-Based Affinity Fusion in Hierarchical Data Association

Author:

Song Young-Min1ORCID,Yoon Young-Chul2,Yoon Kwangjin3,Jang Hyunsung4ORCID,Ha Namkoo4,Jeon Moongu1ORCID

Affiliation:

1. School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea

2. Hyundai Motor Company, Uiwang-si, South Korea

3. SI Analytics Company Ltd., Daejeon, South Korea

4. LIG Nex1 Company Ltd., Yongin-si, South Korea

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Design Strategy for Identification and Tracking of Video Objects Over Crowded Video Scenes using a Novel Feature-Learning Algorithm;2023 3rd International Conference on Mobile Networks and Wireless Communications (ICMNWC);2023-12-04

2. Interaction-Aware Labeled Multi-Bernoulli Filter;IEEE Transactions on Intelligent Transportation Systems;2023-11

3. A Multiple Object Tracker with Spatiotemporal Memory Network;International Journal of Aerospace Engineering;2023-10-26

4. Multi-Object Tracking: Decoupling Features to Solve the Contradictory Dilemma of Feature Requirements;IEEE Transactions on Circuits and Systems for Video Technology;2023-09

5. Online and real-time mask-guided multi-person tracking and segmentation;Pattern Recognition Letters;2023-08

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