Image Segmentation and Feature Extraction for Recognizing Strokes in Tennis Game Videos

Z. Zivkovic, Ferdinand van der Heijden, M. Petkovic, Willem Jonker

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

28 Downloads (Pure)

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 languageUndefined
Title of host publicationProceedings 7th Annual Conference on the Advanced School for Computing and Imaging (ASCI 2001)
EditorsR.L. Langendijk, J.W.J. Heijnsdijk, A.D. Pimentel, M.H.F. Wilkinson
Place of PublicationDelft, the Netherlands
PublisherAdvanced School for Computing and Imaging (ASCI)
Pages262-266
Number of pages5
ISBN (Print)90-803086-6-8
Publication statusPublished - Jun 2001
Event7th Annual Conference of the Advanced School for Computing and Imaging, ASCI 2001 - Heijen, Netherlands
Duration: 30 May 20011 Jun 2001
Conference number: 7

Publication series

Name
PublisherAdvanced School for Computing and Imaging (ASCI)

Conference

Conference7th Annual Conference of the Advanced School for Computing and Imaging, ASCI 2001
Abbreviated titleASCI
CountryNetherlands
CityHeijen
Period30/05/011/06/01

Keywords

  • EWI-7383
  • DB-MMR: MULTIMEDIA RETRIEVAL
  • IR-36135
  • METIS-200955

Cite this