  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.
