Automated bobbing and phase analysis to measure walking entrainment to music

Adolfo López, Carina E. I. Westling, R. Emonet, M. Easteal, L. Lavia, H. Witchel, J. Odobez
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引用次数: 6

Abstract

In this paper, we investigate the influence of music on human walking behaviors in a public setting monitored by surveillance cameras. To this end, we propose a novel algorithm to characterize the frequency and phase of the walk. It relies on a human-by-detection tracking framework, along with a robust fitting of the human head bobbing motion. Preliminary experiments conducted on more than 100 tracks show that an accuracy greater than 85% for foot strike estimation can be achieved, suggesting that large scale analysis is at reach for finer music/walking behavior relationship studies.
自动摆动和相位分析,以测量步行的娱乐音乐
在本文中,我们研究了音乐对人类在公共环境中行走行为的影响。为此,我们提出了一种新的算法来表征行走的频率和相位。它依赖于人类检测跟踪框架,以及对人类头部摆动运动的强大拟合。在超过100个轨道上进行的初步实验表明,可以实现超过85%的脚着地估计精度,这表明更精细的音乐/步行行为关系研究可以进行大规模分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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