Crowd flow estimation from calibrated cameras

被引:0
|
作者
Igor Almeida
Claudio Jung
机构
[1] Federal University of Rio Grande do Sul,
来源
Machine Vision and Applications | 2021年 / 32卷
关键词
Crowd flow; Optical flow; Crowd analysis;
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学科分类号
摘要
Many crowd analysis methods rely on optical flow techniques to estimate the main moving directions. In this work, we propose a crowd flow filtering approach for calibrated cameras that can be coupled to any generic optical flow method. It projects the input optical flow to the world coordinate system, performs a local motion analysis exploring a Social Forces Model and then projects the filtered flow back onto the image plane. The method was tested on publicly available datasets involving crowded scenarios used in conjunction with different optical flow methods, and results indicate that the proposed filtering method provides coherent crowd flows when coupled to the tested methods.
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