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		<doi>10.1109/SIBGRA.2000.883887</doi>
		<citationkey>Torrećo:2000:ShShIn</citationkey>
		<title>Shape from shading and intensity gradient</title>
		<year>2000</year>
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		<author>Torrećo, José R. A.,</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>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<organization>SBC - Brazilian Computer Society</organization>
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		<versiontype>finaldraft</versiontype>
		<keywords>computer vision, shape from shading, intensity gradient, shape estimation, brightness gradient, Green function approach, shape-from-shading, GSFS, single brightness image, uniform disparity field, matching image, linear expansion, reflectance map, surface gradient, closed-form depth map, free parameters, parameter estimation, depth estimate, higher-frequency components, imaged surface, real images, computer vision technique.</keywords>
		<abstract>We present a novel algorithm for shape estimation, using both brightness and brightness gradient as input data. Our algorithm is an improvement of the recently introduced Green's function approach to shape-from-shading (GSFS). In GSFS, we assume that the single brightness image will be matched to a second image through a uniform disparity field, and solve for the matching image via Green's function. When a linear expansion of the reflectance map is considered, the matching image can be related to surface gradient, leading to a closed-form depth map whose free parameters are easily estimated. The author shows that the same procedure can be repeated with the gradient image as input; a second depth estimate thus results which takes into account higher-frequency components of the imaged surface. Extensive experimentation with synthetic and real images corroborates the advantage of the new method.</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/2002/11.04.11.11</url>
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