Frontiers of Computer Science

, Volume 13, Issue 2, pp 426–436 | Cite as

Physical-barrier detection based collective motion analysis

  • Gaoqi He
  • Qi Chen
  • Dongxu Jiang
  • Yubo Yuan
  • Xingjian LuEmail author
Research Article


Collective motion is one of the most fascinating phenomena and mainly caused by the interactions between individuals. Physical-barriers, as the particular facilities which divide the crowd into different lanes, greatly affect the measurement of such interactions. In this paper we propose the physical-barrier detection based collective motion analysis (PDCMA) approach. The main idea is that the interaction between spatially adjacent pedestrians actually does not exist if they are separated by the physical-barrier. Firstly, the physical-barriers are extracted by two-stage clustering. The scene is automatically divided into several motion regions. Secondly, local region collectiveness is calculated to represent the interactions between pedestrians in each region. Finally, extensive evaluations use the three typical methods, i.e., the PDCMA, the Collectiveness, and the average normalized Velocity, to show the efficiency and efficacy of our approach in the scenes with and without physical barriers. Moreover, several escalator scenes are selected as the typical physical-barrier test scenes to demonstrate the performance of our approach. Compared with the current collective motion analysis methods, our approach better adapts to the scenes with physical barriers.


crowd behavior analysis collective motion physical-barrier detection two-stage clustering local region collectiveness 


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This work was funded by the National Key Research and Development Program of China (2016YFA0502300), the National Natural Science Foundation of China (Grant No. 61602175), Shanghai Municipal Commission of Economy and Informatization (150809), the Open Research Funding Program of KLGIS (KLGIS2015A05) and BUAA (BUAAVR-15KF-03), the Fundamental Research Funds for the Central Universities (222201514331), and Green Manufacturing System Integration Project of Ministry of Industry and Technology of China (9908000006).

Supplementary material

11704_2018_7165_MOESM1_ESM.ppt (5 mb)
Physical-barrier detection based collective motion analysis


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Copyright information

© Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Gaoqi He
    • 1
    • 2
  • Qi Chen
    • 1
  • Dongxu Jiang
    • 1
  • Yubo Yuan
    • 1
  • Xingjian Lu
    • 1
    • 3
    Email author
  1. 1.Department of Computer Science and EngineeringEast China University of Science and TechnologyShanghaiChina
  2. 2.State Key Laboratory of Virtual Reality Technology and SystemsBeihang UniversityBeijingChina
  3. 3.Smart City Collaborative Innovation CenterShanghai Jiao Tong UniversityShanghaiChina

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