Automated bobbing and phase analysis to measure walking entrainment to music

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.

An Experimental Study on the Influence of Soundscapes on People’s Behaviour in an Open Public Space

“…Following the protocol of a previous experiment carried out by Witchel and colleagues [10], three instrumental pieces of music from contrasting genres (namely classical, jazz, and ambient electronic music) were used to ensure a high level of inclusiveness, involving different social groups in terms of age and gender [17]. It has been affirmed that conventional acoustic parameters for noise measurement-e.g., weighted sound pressure levels (SPLs)-are not sufficient for the adequate measurement of soundscape [18][19][20][21][22].…”