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	<record>
		<datafield tag="980" ind1=" " ind2=" ">
			<subfield code="a">CONF</subfield>
		</datafield>
		<datafield tag="970" ind1=" " ind2=" ">
			<subfield code="a">Lopez-Mendez_ICIP_2014/IDIAP</subfield>
		</datafield>
		<datafield tag="245" ind1=" " ind2=" ">
			<subfield code="a">Automated Bobbing and Phase Analysis to Measure Walking Entrainment</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Lopez-Mendez, Adolfo</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Westling, C. E. I</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Emonet, Remi</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Easteal, M.</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Lavia, L.</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Witchel, H. J.</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Odobez, Jean-Marc</subfield>
		</datafield>
		<datafield tag="653" ind1="1" ind2=" ">
			<subfield code="a">bobbing estimation</subfield>
		</datafield>
		<datafield tag="653" ind1="1" ind2=" ">
			<subfield code="a">entrainment to music</subfield>
		</datafield>
		<datafield tag="653" ind1="1" ind2=" ">
			<subfield code="a">gait</subfield>
		</datafield>
		<datafield tag="653" ind1="1" ind2=" ">
			<subfield code="a">tracking</subfield>
		</datafield>
		<datafield tag="711" ind1="2" ind2=" ">
			<subfield code="a">IEEE International Conference on Image Processing (ICIP), Paris</subfield>
		</datafield>
		<datafield tag="260" ind1=" " ind2=" ">
			<subfield code="c">2014</subfield>
		</datafield>
		<datafield tag="520" ind1=" " ind2=" ">
			<subfield code="a">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.</subfield>
		</datafield>
	</record>
</collection>