Estimation of crowd density applying wavelet transform and machine learning

Koki Nagao, Daichi Yanagisawa and Katsuhiro Nishinari

Physica A: Statistical Mechanics and its Applications, 2018, vol. 510, issue C, 145-163

Abstract: We conducted a simple experiment in which one pedestrian passed through a crowded area and measured the body-rotational angular velocity with commercial tablets. Then, we developed a new method for predicting crowd density by applying the continuous wavelet transform and machine learning to the data obtained in the experiment. We found that the accuracy of prediction using angular velocity data was as high as that using raw velocity data. Therefore, we concluded that angular velocity has relationship with crowd density and we could estimate crowd density by angular velocity. Our research will contribute to management of safety and comfort of pedestrians by developing an easy way to measure crowd density.

Keywords: Density estimation; Tablet sensor; Wavelet transform; Machine learning; Real experiment (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:510:y:2018:i:c:p:145-163

DOI: 10.1016/j.physa.2018.06.078

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