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		<doi>10.1109/SIBGRAPI.2012.54</doi>
		<citationkey>CeolinHanc:2012:CoGeDi</citationkey>
		<title>Computing gender difference using Fisher-Rao  metric from facial surface normals</title>
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		<year>2012</year>
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		<author>Ceolin, Simone Regina,</author>
		<author>Hancock, Edwin R.,</author>
		<affiliation>Centro Universitário Franciscano </affiliation>
		<affiliation>University of York</affiliation>
		<editor>Freitas, Carla Maria Dal Sasso ,</editor>
		<editor>Sarkar, Sudeep ,</editor>
		<editor>Scopigno, Roberto ,</editor>
		<editor>Silva, Luciano,</editor>
		<e-mailaddress>simoneceolin@gmail.com</e-mailaddress>
		<conferencename>Conference on Graphics, Patterns and Images, 25 (SIBGRAPI)</conferencename>
		<conferencelocation>Ouro Preto, MG, Brazil</conferencelocation>
		<date>22-25 Aug. 2012</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
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		<versiontype>finaldraft</versiontype>
		<keywords>Fisher-Rao metric, surface normal, shape-from-shading.</keywords>
		<abstract>The aim in this paper is  to explore whether the  Fisher-Rao metric can be used to characterise the shape changes due to gender difference.  We work using a 2.5D representation based on facial surface normals (or facial needle-maps) for gender classification. The needle-map is a shape representation which can be acquired from 2D intensity images using shape-from-shading (SFS). Using the von-Mises Fisher distribution, we compute the elements of the Fisher information matrix, and use this to compute geodesic distance between fields of surface normals to construct a shape-space. We embed the fields of facial surface normals into a low dimensional pattern space using a number of alternative methods including multidimensional scaling, heat kernel embedding and commute time embedding.  We present results on clustering the embedded faces using the Max Planck and EAR database.</abstract>
		<language>en</language>
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		<usergroup>simoneceolin@gmail.com</usergroup>
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