Markerless human motion tracking for golf swing application

Sports video tracking is one of the emerging topics that have grabbed a lot of attention due to its high commercial potential. A variety of sports, including tennis, soccer, gymnastics, running, and golf have been utilized to demonstrate new ideas in sports motion tracking. The main challenge for th...

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Bibliographic Details
Main Author:	Sim, Kwoh Fung
Format:	Thesis
Language:	English
Subjects:	Human tracking Sports video tracking Golf Golf swing activity Human motion analysis Athlete activity
Online Access:	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/31916/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/31916/2/Full%20text.pdf
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id	my-unimap-31916
record_format	uketd_dc
spelling	my-unimap-319162014-02-13T13:30:06Z Markerless human motion tracking for golf swing application Sim, Kwoh Fung Sports video tracking is one of the emerging topics that have grabbed a lot of attention due to its high commercial potential. A variety of sports, including tennis, soccer, gymnastics, running, and golf have been utilized to demonstrate new ideas in sports motion tracking. The main challenge for this research work concerns the extraction of a highly complex articulated motion of a golf player performing sports action from a video scene. This research work focuses on developing a markerless human motion tracking system that tracks major body parts of an athlete directly from a sports broadcast video. A hybrid tracking method is proposed in this research work which consists of a combination of three algorithms namely the pyramidal Lucas-Kanade optical flow, normalized correlation based template matching and background subtraction. These algorithms are used to track the head, body, hands, shoulders, knees and the feet of a golfer while the individual is performing a full swing. Finally, the output results are tracked and mapped onto a 2D articulated human stick model to represent the pose of the golfer. The research work has been tested on a broadcast video of a golfer on various background complexities. Universiti Malaysia Perlis (UniMAP) 2011 Thesis en http://dspace.unimap.edu.my:80/dspace/handle/123456789/31916 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/31916/1/Page%201-24.pdf ff374810b48bb41965f28f747938492f http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/31916/2/Full%20text.pdf 8dd6bb07a6b07e5aec3f4d634bafd7b0 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/31916/3/license.txt 8a4605be74aa9ea9d79846c1fba20a33 Human tracking Sports video tracking Golf Golf swing activity Human motion analysis Athlete activity School of Mechatronic Engineering
institution	Universiti Malaysia Perlis
collection	UniMAP Institutional Repository
language	English
topic	Human tracking Sports video tracking Golf Golf swing activity Human motion analysis Athlete activity
spellingShingle	Human tracking Sports video tracking Golf Golf swing activity Human motion analysis Athlete activity Sim, Kwoh Fung Markerless human motion tracking for golf swing application
description	Sports video tracking is one of the emerging topics that have grabbed a lot of attention due to its high commercial potential. A variety of sports, including tennis, soccer, gymnastics, running, and golf have been utilized to demonstrate new ideas in sports motion tracking. The main challenge for this research work concerns the extraction of a highly complex articulated motion of a golf player performing sports action from a video scene. This research work focuses on developing a markerless human motion tracking system that tracks major body parts of an athlete directly from a sports broadcast video. A hybrid tracking method is proposed in this research work which consists of a combination of three algorithms namely the pyramidal Lucas-Kanade optical flow, normalized correlation based template matching and background subtraction. These algorithms are used to track the head, body, hands, shoulders, knees and the feet of a golfer while the individual is performing a full swing. Finally, the output results are tracked and mapped onto a 2D articulated human stick model to represent the pose of the golfer. The research work has been tested on a broadcast video of a golfer on various background complexities.
format	Thesis
author	Sim, Kwoh Fung
author_facet	Sim, Kwoh Fung
author_sort	Sim, Kwoh Fung
title	Markerless human motion tracking for golf swing application
title_short	Markerless human motion tracking for golf swing application
title_full	Markerless human motion tracking for golf swing application
title_fullStr	Markerless human motion tracking for golf swing application
title_full_unstemmed	Markerless human motion tracking for golf swing application
title_sort	markerless human motion tracking for golf swing application
granting_institution	Universiti Malaysia Perlis (UniMAP)
granting_department	School of Mechatronic Engineering
url	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/31916/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/31916/2/Full%20text.pdf
_version_	1747836794640007168

Markerless human motion tracking for golf swing application

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