Abstract
This paper addresses the problem of recognizing human
actions from video. Particularly, the case of recognizing
events in tennis game videos is analyzed. Driven by our
domain knowledge, a robust player segmentation
algorithm is developed for real video data. Further, we
introduce a number of novel features to be extracted for
our particular application. Different feature combinations
are investigated in order to find the optimal one. Finally,
recognition results for different classes of tennis strokes
using automatic learning capability of Hidden Markov
Models (HMMs) are presented. The experimental results
demonstrate that our method is close to realizing statistics
of tennis games automatically using ordinary TV
broadcast videos.
Original language | Undefined |
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Title of host publication | Proceedings 7th Annual Conference on the Advanced School for Computing and Imaging (ASCI 2001) |
Editors | R.L. Langendijk, J.W.J. Heijnsdijk, A.D. Pimentel, M.H.F. Wilkinson |
Place of Publication | Delft, the Netherlands |
Publisher | Advanced School for Computing and Imaging (ASCI) |
Pages | 262-266 |
Number of pages | 5 |
ISBN (Print) | 90-803086-6-8 |
Publication status | Published - Jun 2001 |
Event | 7th Annual Conference of the Advanced School for Computing and Imaging, ASCI 2001 - Heijen, Netherlands Duration: 30 May 2001 → 1 Jun 2001 Conference number: 7 |
Publication series
Name | |
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Publisher | Advanced School for Computing and Imaging (ASCI) |
Conference
Conference | 7th Annual Conference of the Advanced School for Computing and Imaging, ASCI 2001 |
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Abbreviated title | ASCI |
Country/Territory | Netherlands |
City | Heijen |
Period | 30/05/01 → 1/06/01 |
Keywords
- EWI-7383
- DB-MMR: MULTIMEDIA RETRIEVAL
- IR-36135
- METIS-200955