Measuring Handball Players Trajectories Using An Automatically Trained Boosting Algorithm.

dc.creatorBarros, Ricardo M L
dc.creatorMenezes, Rafael P
dc.creatorRussomanno, Tiago G
dc.creatorMisuta, Milton S
dc.creatorBrandão, Bruno C
dc.creatorFigueroa, Pascual J
dc.creatorLeite, Neucimar J
dc.creatorGoldenstein, Siome K
dc.date2011
dc.date2015-11-27T13:22:14Z
dc.date2015-11-27T13:22:14Z
dc.date.accessioned2018-03-29T01:14:31Z
dc.date.available2018-03-29T01:14:31Z
dc.identifierComputer Methods In Biomechanics And Biomedical Engineering. v. 14, n. 1, p. 53-63, 2011.
dc.identifier1476-8259
dc.identifier10.1080/10255842.2010.494602
dc.identifierhttp://www.ncbi.nlm.nih.gov/pubmed/21161798
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/199788
dc.identifier21161798
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1300021
dc.descriptionThe aim of the present paper is to propose and evaluate an automatically trained cascaded boosting detector algorithm based on morphological segmentation for tracking handball players. The proposed method was able to detect correctly 84% of players when applied to the second period of that same game used for training and 74% when applied to a different game. Furthermore, the analysis of the automatic training using boosting detector revealed general results such as the training time initially increased with the number of figures used, but as more figures were added, the training time decreased. Automatic morphological segmentation has shown to be a fast and efficient method for selecting image regions for the boosting detector and allowed an improvement in the automatic tracking of handball players.
dc.description14
dc.description53-63
dc.languageeng
dc.relationComputer Methods In Biomechanics And Biomedical Engineering
dc.relationComput Methods Biomech Biomed Engin
dc.rightsfechado
dc.rights
dc.sourcePubMed
dc.subjectAlgorithms
dc.subjectArm
dc.subjectCalibration
dc.subjectHumans
dc.subjectSports
dc.titleMeasuring Handball Players Trajectories Using An Automatically Trained Boosting Algorithm.
dc.typeArtículos de revistas


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