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		<citationkey>GonçalvesMoSiMaOdPi:2007:MuMiTr</citationkey>
		<author>Gonçalves, Wesley Nunes,</author>
		<author>Monteiro, João Bosco Oliveira,</author>
		<author>Silva, Jonathan de Andrade,</author>
		<author>Machado, Bruno Brandoli,</author>
		<author>Odakura, Valguima,</author>
		<author>Pistori, Hemerson,</author>
		<affiliation>Dom Bosco Catholic University</affiliation>
		<affiliation>Dom Bosco Catholic University</affiliation>
		<affiliation>Dom Bosco Catholic University</affiliation>
		<affiliation>Dom Bosco Catholic University</affiliation>
		<affiliation>TecSinapse - Tecnologia da Informação Ltda</affiliation>
		<affiliation>Dom Bosco Catholic University</affiliation>
		<title>Multiple mice tracking using a combination of Particle Filter and K-Means</title>
		<conferencename>Brazilian Symposium on Computer Graphics and Image Processing, 20 (SIBGRAPI)</conferencename>
		<year>2007</year>
		<editor>Falcão, Alexandre Xavier,</editor>
		<editor>Lopes, Hélio Côrtes Vieira,</editor>
		<booktitle>Proceedings</booktitle>
		<date>Oct. 7-10, 2007</date>
		<publisheraddress>Los Alamitos</publisheraddress>
		<publisher>IEEE Computer Society</publisher>
		<conferencelocation>Belo Horizonte</conferencelocation>
		<keywords>Particle filter, mice, k-means, tracking.</keywords>
		<abstract>This paper presents a new approach to multiple objects tracking that combines particle filters and k-means. The approach has been tested under an important real world situation, related to pharmacological development, which has also proved to serve as an interesting ground-truth dataset provider for the evaluation of tracking algorithms. The obtained results are then compared to other models. The promising results of these experiments are presented.</abstract>
		<language>en</language>
		<tertiarytype>Full Paper</tertiarytype>
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