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  4. A Graphical Social Topology Model for RGB-D Multi-Person Tracking
 
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2021
  • Zeitschriftenaufsatz

Titel

A Graphical Social Topology Model for RGB-D Multi-Person Tracking

Abstract
Tracking multiple persons is a challenging task especially when persons move in groups and occlude one another. Existing research have investigated the problems of group division and segmentation; however, lacking overall person-group topology modeling limits the ability to handle complex person and group dynamics. We propose a Graphical Social Topology (GST) model in the RGB-D data domain, and estimate object group dynamics by jointly modeling the group structure and states of persons using RGB-D topological representation. With our topology representation, moving persons are not only assigned to groups, but also dynamically connected with each other, which enables in-group individuals to be correctively associated and the cohesion of each group to be precisely modeled. Using the learned typical topology pattern and group online update modules, we infer the birth/death and merging/splitting of dynamic groups. With the GST model, the proposed multi-person tracker can naturally facilitate the occlusion problem by treating the occluded object and other in-group members as a whole, while leveraging overall state transition. Experiments on different RGB-D and RGB datasets confirm that the proposed multi-person tracker improves the state-of-the-arts.
Author(s)
Gao, Shan
Northwestern Polytechnical Univ. / Tsinghua Univ.
Ye, Qixiang
Univ. of Chinese Academy of Sciences
Liu, Li
National Univ. of Defense Technology, China / Univ. of Oulu
Kuijper, Arjan
Fraunhofer-Institut für Graphische Datenverarbeitung IGD
Ji, Xiangyang
Tsinghua Univ.
Zeitschrift
IEEE transactions on circuits and systems for video technology
Thumbnail Image
DOI
10.1109/TCSVT.2021.3049397
Language
Englisch
google-scholar
IGD
Tags
  • topology

  • feature extraction

  • data models

  • Lead Topic: Smart Cit...

  • Research Line: Comput...

  • model-based tracking

  • object tracking

  • people tracking

  • network topologies

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