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VM-tracking: Visual-motion sensing integration for real-time human tracking
Zhai, Qiang1; Ding, Sihao2; Li, Xinfeng1; Yang, Fan1; Teng, Jin1; Zhu, Junda3; Xuan, Dong1; Zheng, Yuan F.2; Zhao, Wei3
2015-08-21
Conference Name34th IEEE Annual Conference on Computer Communications and Networks, IEEE INFOCOM 2015
Source PublicationProceedings - IEEE INFOCOM
Volume26
Pages711-719
Conference Date4 26, 2015 - 5 1, 2015
Conference PlaceHong Kong, Hong kong
Author of SourceInstitute of Electrical and Electronics Engineers Inc.
AbstractHuman tracking in video has many practical applications such as visual guided navigation, assisted living, etc. In such applications, it is necessary to accurately track multiple humans across multiple cameras, subject to real-time constraints. Despite recent advances in visual tracking research, the tracking systems purely relying on visual information fail to meet the accuracy and real-time requirements at the same time. In this paper, we present a novel accurate and real-time human tracking system called VM-Tracking. The system aggregates the information of motion (M) sensor on human, and integrates it with visual (V) data based on physical locations. The system has two key features, i.e. location-based VM fusion and appearance-free tracking, which significantly distinguish itself from other existing human tracking systems. We have implemented the VM-Tracking system and conducted comprehensive experiments on challenging scenarios. © 2015 IEEE.
DOI10.1109/INFOCOM.2015.7218440
Language英语
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Document TypeConference paper
CollectionUniversity of Macau
Affiliation1.Department of Computer Science and Engineering, Ohio State University, United States;
2.Department of Electrical and Computer Engineering, Ohio State University, United States;
3.University of Macau, China
Recommended Citation
GB/T 7714
Zhai, Qiang,Ding, Sihao,Li, Xinfeng,et al. VM-tracking: Visual-motion sensing integration for real-time human tracking[C]//Institute of Electrical and Electronics Engineers Inc.,2015:711-719.
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