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		<doi>10.1109/SIBGRAPI.2015.10</doi>
		<citationkey>PáduaPáduPereSous:2015:PaFiPr</citationkey>
		<title>Particle filter-based predictive tracking of futsal players from a single stationary camera</title>
		<format>On-line</format>
		<year>2015</year>
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		<author>Pádua, Pedro Henrique Caetano de,</author>
		<author>Pádua, Flávio Luis Cardeal,</author>
		<author>Pereira, Marconi de Arruda,</author>
		<author>Sousa, Marco Túlio Diniz,</author>
		<affiliation>Centro Federal de Educação Tecnológica de Minas Gerais</affiliation>
		<affiliation>Centro Federal de Educação Tecnológica de Minas Gerais</affiliation>
		<affiliation>Universidade Federal de São João del-Rei</affiliation>
		<affiliation>Centro Federal de Educação Tecnológica de Minas Gerais</affiliation>
		<editor>Papa, João Paulo,</editor>
		<editor>Sander, Pedro Vieira,</editor>
		<editor>Marroquim, Ricardo Guerra,</editor>
		<editor>Farrell, Ryan,</editor>
		<e-mailaddress>pedhenrique@decom.cefetmg.br</e-mailaddress>
		<conferencename>Conference on Graphics, Patterns and Images, 28 (SIBGRAPI)</conferencename>
		<conferencelocation>Salvador, BA, Brazil</conferencelocation>
		<date>26-29 Aug. 2015</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>player tracking, particle filter, futsal, tactical and physical analyses.</keywords>
		<abstract>In this paper we study the use of computer vision techniques for visual tracking of futsal players. In the sports field, player tracking is an important task, as it can provide an estimate of the position of the athlete in a given time and thus compute his/her trajectories. This information can be used by coaches and sport professionals on tactical and physical analyses. We use adaptive background subtraction and blob analysis to detect players, as well as particle filters to predict their positions and track them using data from a single stationary camera. Experimental results show that our approach is capable to track players and compute their trajectories over time with errors below 20 cm, thus demonstrating a high potential to be used in a wide range of futsal match analyses.</abstract>
		<language>en</language>
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