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		<doi>10.1109/SIBGRA.2000.883889</doi>
		<citationkey>FerisCesa:2000:TrFaFe</citationkey>
		<title>Tracking facial features using Gabor wavelet networks</title>
		<year>2000</year>
		<numberoffiles>1</numberoffiles>
		<size>641 KiB</size>
		<author>Feris, Rogério S.,</author>
		<author>Cesar Junior, Roberto M.,</author>
		<editor>Carvalho, Paulo Cezar Pinto,</editor>
		<editor>Walter, Marcelo,</editor>
		<conferencename>Brazilian Symposium on Computer Graphics and Image Processing, 13 (SIBGRAPI)</conferencename>
		<conferencelocation>Gramado, RS, Brazil</conferencelocation>
		<date>17-20 Oct. 2000</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<pages>22-27</pages>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<organization>SBC - Brazilian Computer Society</organization>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<keywords>optical tracking, video sequences, Gabor wavelet networks, automatic facial feature tracking, discrete face template, linear combination, continuous 2D odd-Gabor wavelet functions, 2D parameters, image information, homogeneous illumination changes, affine deformations, face image, tracking approach, face geometry, facial feature deformations, eye blinking, smiling, computational resources, real time processing.</keywords>
		<abstract>The work presents a method for automatic facial feature tracking in video sequences. In this method, a discrete face template is represented as a linear combination of continuous 2D odd-Gabor wavelet functions. The weights and 2D parameters (position, scale and orientation) of each wavelet are determined optimally so that the maximum amount of image information is preserved for a given number of wavelets. We have used this representation to achieve effective facial feature tracking that is robust to homogeneous illumination changes and affine deformations of the face image. Moreover, the tracking approach considers the overall geometry of the face, being robust to facial feature deformations such as eye blinking and smiling. The number of wavelets in the representation may be chosen with respect to the available computational resources, even allowing real time processing.</abstract>
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		<notes>The conference was held in Gramado, RS, Brazil, from October 17 to 20.</notes>
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		<url>http://sibgrapi.sid.inpe.br/rep-/sid.inpe.br/banon/2002/11.04.11.57</url>
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