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dc.contributor.authorBarris, Sianen_NZ
dc.contributor.authorButton, Cen_NZ
dc.contributor.authorKennedy, Gen_NZ
dc.date.available2011-04-07T03:03:00Z
dc.date.copyright2007-12-06en_NZ
dc.identifier.citationBarris, S., Button, C., & Kennedy, G. (2007, December 6). Development of an automated tracking system for analysis of human movement. Presented at the 19th Annual Colloquium of the Spatial Information Research Centre (SIRC 2007: Does Space Matter?).en
dc.identifier.urihttp://hdl.handle.net/10523/775
dc.descriptionOnly the abstract was published in the proceedings. There is no full text.en_NZ
dc.description.abstractTo understand the mechanisms underlying a successful team, one must first understand the circumstances leading to successful performance outcomes (i.e., point/goal scoring events). However, tracking player performance in team sports is difficult as games involve quick, agile movements, with many unpredictable changes in direction and frequent collisions between players. Manual tracking can be a subjective and an often laborious process which has arguably discouraged researchers from conducting more detailed analyses of the multiple players’ interactions within games. The current challenge is to obtain appropriate video sequences that can robustly identify and label people over time, in an indoor environment containing multiple interacting players. Therefore the aim of this investigation is to develop an automated, motion detection system capable of tracking the global movements of two basketball teams and the ball on an indoor court. A basketball playing court was recorded using one static overhead camera and player movements were identified by automated motion detection software. This software provided the x, y coordinates of each individual player and the ball, and players were assigned to one of two teams using colour recognition of team uniforms. Individual player coordinates were then tracked over time and used to provide spatio-temporal trajectories (maps) of player movements and event frequencies. The analysis of these variables can be used to compare playing sequences (i.e. throw in to scoring opportunity; or turnover to scoring opportunity) to determine if common movement patterns exist in team behaviour.en_NZ
dc.format.mimetypeapplication/pdf
dc.relation.urihttp://www.business.otago.ac.nz/sirc/conferences/2007/16_barris.pdfen_NZ
dc.subject.lcshQA76 Computer softwareen_NZ
dc.titleDevelopment of an automated tracking system for analysis of human movementen_NZ
dc.typeConference or Workshop Item (Oral presentation)en_NZ
dc.description.versionPublisheden_NZ
otago.date.accession2009-04-21 21:47:51en_NZ
otago.relation.pages81en_NZ
otago.openaccessOpen
dc.identifier.eprints812en_NZ
dc.description.refereedNon Peer Revieweden_NZ
otago.school.eprintsSpatial Information Research Centreen_NZ
otago.school.eprintsSchool of Physical Educationen_NZ
otago.event.dates6-7 Decemberen_NZ
otago.event.placeDunedin, New Zealanden_NZ
otago.event.typeconferenceen_NZ
otago.event.title19th Annual Colloquium of the Spatial Information Research Centre (SIRC 2007: Does Space Matter?)en_NZ
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