Recognizing Strokes in Tennis Videos Using Hidden Markov Models

M. Petkovic, Willem Jonker, Z. Zivkovic

Research output: Contribution to conferencePaper

Abstract

This paper addresses content-based video retrieval with an emphasis on recognizing events in tennis game videos. In particular, we aim at recognizing different classes of tennis strokes using automatic learning capability of Hidden Markov Models. 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. The experimental results demonstrate that our method is close to realizing statistics of tennis games automatically using ordinary TV broadcast videos.
Original languageUndefined
Pages512-516
Number of pages5
Publication statusPublished - Sep 2001
EventIASTED International Conference on Visualization, Imaging and Image Processing, VIIP 2001 - Marbella, Spain
Duration: 3 Sep 20015 Sep 2001

Conference

ConferenceIASTED International Conference on Visualization, Imaging and Image Processing, VIIP 2001
Abbreviated titleVIIP
CountrySpain
CityMarbella
Period3/09/015/09/01

Keywords

  • DB-MMR: MULTIMEDIA RETRIEVAL
  • EWI-7307
  • IR-63521

Cite this

Petkovic, M., Jonker, W., & Zivkovic, Z. (2001). Recognizing Strokes in Tennis Videos Using Hidden Markov Models. 512-516. Paper presented at IASTED International Conference on Visualization, Imaging and Image Processing, VIIP 2001, Marbella, Spain.