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7383 Image Segmentation and Feature Extraction for Recognizing Strokes in Tennis Game Videos
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Zivkovic, Z. and van der Heijden, F. and Petkovic, M. and Jonker, W. (2001) Image Segmentation and Feature Extraction for Recognizing Strokes in Tennis Game Videos. In: Proceedings 7th Annual Conference on the Advanced School for Computing and Imaging (ASCI 2001), 30 May - 1 June 2001, Heijen, The Netherlands. ASCI. ISBN 90-803086-6-8

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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.

Item Type:Conference or Workshop Paper (Full Paper, Talk)
Research Group:EWI-DB: Databases, EWI-SAS: Signals and Systems
Research Program:CTIT-NICE: Natural Interaction in Computer-mediated Environments
Research Project:DMW: Digital Media Warehousing
Additional Information:Imported from EWI/DB PMS [db-utwente:inpr:0000003221]
ID Code:7383
Status:Published
Deposited On:05 February 2007
Refereed:Yes
International:Yes
More Information:statistics

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