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			<subfield code="a">CONF</subfield>
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			<subfield code="a">Funes_ICIP2013/IDIAP</subfield>
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		<datafield tag="245" ind1=" " ind2=" ">
			<subfield code="a">Person Independent 3D Gaze Estimation From Remote RGB-D Cameras</subfield>
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		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Funes Mora, Kenneth Alberto</subfield>
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		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Odobez, Jean-Marc</subfield>
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		<datafield tag="856" ind1="4" ind2="0">
			<subfield code="i">EXTERNAL</subfield>
			<subfield code="u">http://publications.idiap.ch/attachments/papers/2013/Funes_ICIP2013.pdf</subfield>
			<subfield code="x">PUBLIC</subfield>
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		<datafield tag="711" ind1="2" ind2=" ">
			<subfield code="a">International Conference on Image Processing</subfield>
			<subfield code="c">Melbourne, Australia</subfield>
		</datafield>
		<datafield tag="260" ind1=" " ind2=" ">
			<subfield code="c">2013</subfield>
			<subfield code="b">IEEE</subfield>
		</datafield>
		<datafield tag="024" ind1="7" ind2=" ">
			<subfield code="a">10.1109/ICIP.2013.6738574</subfield>
			<subfield code="2">doi</subfield>
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		<datafield tag="520" ind1=" " ind2=" ">
			<subfield code="a">We address the problem of person independent 3D gaze estimation using a remote, low resolution, RGB-D camera. The approach relies on a sparse technique to reconstruct normalized eye test images from a gaze appearance model (a set of eye image/gaze pairs) and infer their gaze accordingly. In this context, the paper makes three contributions:  (i) unlike most previous approaches, we exploit the coupling (and constraints) between both eyes to infer their gaze jointly; (ii)  we show that a generic gaze appearance model built from the aggregation of person-specific models can be used to handle unseen users and compensate for appearance variations across people, since a test user eyes' appearance will be reconstructed from similar users within the generic model.
(iii) we propose an automatic model selection method that leads to comparable performance with a reduced computational load.</subfield>
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