Crowd Density Field Estimation Based on Crowd Dynamics Theory and Social Force Model. Issue 3 (1st May 2019)

• Record Type: Journal Article
• Authors: Wei, Xinlei; Du, Junping; Liang, Meiyu; Xue, Zhe
• Is Part Of: Chinese journal of electronics. Volume 28:Issue 3(2019)
• Page Start: 521
• Page End: 528
• Publication Date: 2019-05-01
• Subjects: Social force model -- Crowd dynamics -- Crowd density field -- Computer vision; feature extraction -- object detection -- video surveillance; crowd density field model -- crowd density field estimation -- crowd dynamics theory -- social force model -- local crowd density -- crowd distribution estimation tasks -- high performance estimation model; Electronics -- Periodicals; Electronics -- China -- Periodicals; Electronics; China; Periodicals; 621.38105
• DOI: 10.1049/cje.2019.03.021
• Languages: English
• ISSNs: 1022-4653

Abstract

Abstract : 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 high‐performance 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.