Automatic parsing of ball-sports video sequences and its application to soccer
This thesis describes the study, proposal and design of a video model using a priori knowledge to parse generic ball-sports video sequences and automatically classify them into proper play categories based on their contextual information. An automatic video parser has been implemented using the prop...
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2010
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sg-ntu-dr.10356-390022023-07-04T16:01:45Z Automatic parsing of ball-sports video sequences and its application to soccer Lim, Teck Sin. Gong, Yihong School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electric apparatus and materials This thesis describes the study, proposal and design of a video model using a priori knowledge to parse generic ball-sports video sequences and automatically classify them into proper play categories based on their contextual information. An automatic video parser has been implemented using the proposed video model on a specific ball-sports game - soccer. Extensive experimental results showed that our proposed video model is effective. Tests on 720 soccer video clips of 18 play categories have a recognition rate of 87.7%. Master of Engineering 2010-05-21T03:39:40Z 2010-05-21T03:39:40Z 1997 1997 Thesis http://hdl.handle.net/10356/39002 NANYANG TECHNOLOGICAL UNIVERSITY 127 p. application/pdf |
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Singapore Singapore |
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DRNTU::Engineering::Electrical and electronic engineering::Electric apparatus and materials |
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DRNTU::Engineering::Electrical and electronic engineering::Electric apparatus and materials Lim, Teck Sin. Automatic parsing of ball-sports video sequences and its application to soccer |
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This thesis describes the study, proposal and design of a video model using a priori knowledge to parse generic ball-sports video sequences and automatically classify them into proper play categories based on their contextual information. An automatic video parser has been implemented using the proposed video model on a specific ball-sports game - soccer. Extensive experimental results showed that our proposed video model is effective. Tests on 720 soccer video clips of 18 play categories have a recognition rate of 87.7%. |
| author2 |
Gong, Yihong |
| author_facet |
Gong, Yihong Lim, Teck Sin. |
| format |
Theses and Dissertations |
| author |
Lim, Teck Sin. |
| author_sort |
Lim, Teck Sin. |
| title |
Automatic parsing of ball-sports video sequences and its application to soccer |
| title_short |
Automatic parsing of ball-sports video sequences and its application to soccer |
| title_full |
Automatic parsing of ball-sports video sequences and its application to soccer |
| title_fullStr |
Automatic parsing of ball-sports video sequences and its application to soccer |
| title_full_unstemmed |
Automatic parsing of ball-sports video sequences and its application to soccer |
| title_sort |
automatic parsing of ball-sports video sequences and its application to soccer |
| publishDate |
2010 |
| url |
http://hdl.handle.net/10356/39002 |
| _version_ |
1772827134940676096 |