WEI Xinlei, DU Junping, LIANG Meiyu, et al., “Crowd Density Field Estimation Based on Crowd Dynamics Theory and Social Force Model,” Chinese Journal of Electronics, vol. 28, no. 3, pp. 521-528, 2019, doi: 10.1049/cje.2019.03.021
Citation: WEI Xinlei, DU Junping, LIANG Meiyu, et al., “Crowd Density Field Estimation Based on Crowd Dynamics Theory and Social Force Model,” Chinese Journal of Electronics, vol. 28, no. 3, pp. 521-528, 2019, doi: 10.1049/cje.2019.03.021

Crowd Density Field Estimation Based on Crowd Dynamics Theory and Social Force Model

doi: 10.1049/cje.2019.03.021
Funds:  This work is supported by the National Natural Science Foundation of China(No.61532006, No.61772083, No.61877006, No.61802028).
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  • Corresponding author: DU Junping (corresponding author) was born in 1963. She is now a full professor and Ph.D. supervisor in School of Computer Science and Technology, Beijing University of Posts and Telecommunications. Her research interests include artificial intelligence, image processing and pattern recognition. (Email:junpingdu@126.com)
  • Received Date: 2017-05-18
  • Publish Date: 2019-05-10
  • The local crowd density and the crowd distribution estimation tasks are useful but challenging. There are two main problems which limit the performance of existing algorithms. The first one is that there are not enough labeled training samples to build the highperformance estimation model. Another one is that existing methods lack the supports of physical theories of the crowd. To remedy them, a novel crowd density field model is proposed, which is deduced by jointing crowd dynamics theory and social force model. A crowd counting method based on the proposed crowd density field model is introduced to measure the proposed crowd density field model. Extensive experiments confirm the effectiveness of the proposed plan.
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