Robust player gesture spotting and recognition in low-resolution sports video

Myung Cheol Roh, Bill Christmas, Joseph Kittler, Seong Whan Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Citations (Scopus)

Abstract

The determination of the player's gestures and actions in sports video is a key task in automating the analysis of the video material at a high level. In many sports views, the camera covers a large part of the sports arena, so that the resolution of player's region is low. This makes the determination of the player's gestures and actions a challenging task, especially if there is large camera motion. To overcome these problems, we propose a method based on curvature scale space templates of the player's silhouette. The use of curvature scale space makes the method robust to noise and our method is robust to significant shape corruption of a part of player's silhouette. We also propose a new recognition method which is robust to noisy sequences of data and needs only a small amount of training data.

Original languageEnglish
Title of host publicationComputer Vision - ECCV 2006, 9th European Conference on Computer Vision, Proceedings
Pages347-358
Number of pages12
DOIs
Publication statusPublished - 2006
Event9th European Conference on Computer Vision, ECCV 2006 - Graz, Austria
Duration: 2006 May 72006 May 13

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3954 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th European Conference on Computer Vision, ECCV 2006
Country/TerritoryAustria
CityGraz
Period06/5/706/5/13

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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