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		<doi>10.1109/SIBGRA.2004.1352945</doi>
		<citationkey>JungKelb:2004:RoLiMo</citationkey>
		<title>A Robust Linear-Parabolic Model for Lane Following</title>
		<format>On-line</format>
		<year>2004</year>
		<numberoffiles>1</numberoffiles>
		<size>353 KiB</size>
		<author>Jung, Cláudio Rosito,</author>
		<author>Kelber, Christian Roberto,</author>
		<affiliation>UNISINOS - Universidade do Vale do Rio dos Sinos - Ciências Exatas e Tecnológicas</affiliation>
		<editor>Araújo, Arnaldo de Albuquerque,</editor>
		<editor>Comba, João Luiz Dihl,</editor>
		<editor>Navazo, Isabel,</editor>
		<editor>Sousa, Antônio Augusto de,</editor>
		<e-mailaddress>crjung@exatas.unisinos.br</e-mailaddress>
		<conferencename>Brazilian Symposium on Computer Graphics and Image Processing, 17 (SIBGRAPI) - Ibero-American Symposium on Computer Graphics, 2 (SIACG)</conferencename>
		<conferencelocation>Curitiba, PR, Brazil</conferencelocation>
		<date>17-20 Oct. 2004</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<keywords>lane detection, lane tracking, video sequence, Hough Transform, linear-parabolic model.</keywords>
		<abstract>In this paper, we address the problem of lane detection and lane tracking. A linear model is used to approximate lane boundaries in the first frame of a video sequence, using a combination of the edge distribution function and the Hough Transform. A new linear-parabolic model is used in the subsequent frames: the linear part of the model is used to fit the near vision field, while the parabolic model fits the far field. The proposed technique demands low computational power and memory requirements, and showed to be robust in the presence of noise, shadows, lack of lane painting and change of illumination conditions.</abstract>
		<language>en</language>
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