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	<record>
		<datafield tag="980" ind1=" " ind2=" ">
			<subfield code="a">CONF</subfield>
		</datafield>
		<datafield tag="970" ind1=" " ind2=" ">
			<subfield code="a">FunesMora_ICMI_DC_2013/IDIAP</subfield>
		</datafield>
		<datafield tag="245" ind1=" " ind2=" ">
			<subfield code="a">3D Head Pose and Gaze Tracking and Their Application to Diverse Multimodal Tasks</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Funes Mora, Kenneth Alberto</subfield>
		</datafield>
		<datafield tag="653" ind1="1" ind2=" ">
			<subfield code="a">Gaze estimation</subfield>
		</datafield>
		<datafield tag="653" ind1="1" ind2=" ">
			<subfield code="a">HCI</subfield>
		</datafield>
		<datafield tag="653" ind1="1" ind2=" ">
			<subfield code="a">Head pose tracking</subfield>
		</datafield>
		<datafield tag="653" ind1="1" ind2=" ">
			<subfield code="a">HHI</subfield>
		</datafield>
		<datafield tag="653" ind1="1" ind2=" ">
			<subfield code="a">HRI</subfield>
		</datafield>
		<datafield tag="653" ind1="1" ind2=" ">
			<subfield code="a">Speech</subfield>
		</datafield>
		<datafield tag="711" ind1="2" ind2=" ">
			<subfield code="a">Doctoral consortium of the 15th ACM International Conference on Multimodal Interaction</subfield>
			<subfield code="c">Sydney, Australia</subfield>
		</datafield>
		<datafield tag="260" ind1=" " ind2=" ">
			<subfield code="c">2013</subfield>
		</datafield>
		<datafield tag="024" ind1="7" ind2=" ">
			<subfield code="a">10.1145/2522848.2532192</subfield>
			<subfield code="2">doi</subfield>
		</datafield>
		<datafield tag="520" ind1=" " ind2=" ">
			<subfield code="a">In this PhD thesis the problem of 3D head pose and gaze tracking from minimal user cooperation is addressed. By exploiting characteristics of RGB-D sensors, contributions
have been made related to consequent problems of the lack of cooperation: in particular, head pose and inter-person appearance variability; in addition to low resolution handling. The resulting system enabled diverse multimodal applications. In particular, recent work combined multiple RGB-D sensors to detect gazing events in dyadic interactions.
The research plan consists of: i) Improving the robustness, accuracy and usability of the head pose and gaze tracking system; ii) To use additional multimodal cues, such as speech and dynamic context, to train and adapt gaze models in an unsupervised manner; iii) To extend the application of 3D gaze estimation to diverse multimodal applications. This includes visual focus of attention tasks involving multiple visual targets, e.g. people in a meeting-like setup.</subfield>
		</datafield>
	</record>
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