Single player tracking in multiple sports videos
Added Title
Mechatronics and Machine Vision in Practice (21st : 2015)
Annual International Conference on Mechatronics and Machine Vision in Practice (22nd : 2015)
College
College of Computer Studies
Department/Unit
Computer Technology
Document Type
Book
Source Title
Mechatronics and Machine Vision in Practice 3
First Page
73
Last Page
89
Publication Date
4-4-2018
Abstract
Performance analysis for basketball development programs are based on the athletes' movement patterns, playing position on an area, and ball acquisition. The objective of the system is to automate the performance analysis by providing raw statistical data based on the player's behaviors produced through tracking the player inside the basketball court. Using visual features described by SURF, unoccluded players are localized using a tracking by detection approach with an observed accuracy of 40%. Player positions are also adjusted to compensate for distortions, which improves player localization by 0.11%, on average. © Springer International Publishing AG, part of Springer Nature 2018.
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Digitial Object Identifier (DOI)
10.1007/978-3-319-76947-9_6
Recommended Citation
Petilla, C. B., Yap, G. G., Zheng, N. Y., Yuson, P. L., & Ilao, J. P. (2018). Single player tracking in multiple sports videos. Mechatronics and Machine Vision in Practice 3, 73-89. https://doi.org/10.1007/978-3-319-76947-9_6
Disciplines
Graphics and Human Computer Interfaces
Keywords
Pattern recognition systems; Human activity recognition
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Note
Presented at the 21st Mechatronics and Machine Vision in Practice, M2VIP 2015 and the 22nd Annual International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2015