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Highlight events detection in soccer video using HCRF

  • Xi'an Jiaotong University

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

12 Scopus citations

Abstract

Highlight event detection is a fundamental step of semantic based video retrieval and personalized sports video browsing. In this paper, an effective hidden conditional random fields (HCRFs) based soccer video event detection method is proposed. Firstly, soccer video is classified into clips with middle level semantics. The middle level semantics are further refined into more meaningful categories in terms of camera motion information. Then the continuous soccer video sequence is classified into sequential event clips based on the transitions of middle level semantics. HCRFs are utilized to model the four highlight events (goal, shoot, foul, and placed kick) and a normal kick. Comparisons are made with the dynamic Bayesian networks (DBN) and conditional random fields (CRF) based event detection approaches. Experimental results show the effectiveness of the proposed method.

Original languageEnglish
Title of host publicationProceedings of the 2nd International Conference on Internet Multimedia Computing and Service, ICIMCS'10
Pages171-174
Number of pages4
DOIs
StatePublished - 2010
Event2nd International Conference on Internet Multimedia Computing and Service, ICIMCS 2010 - Harbin, China
Duration: 30 Dec 201031 Dec 2010

Publication series

NameProceedings of the 2nd International Conference on Internet Multimedia Computing and Service, ICIMCS'10

Conference

Conference2nd International Conference on Internet Multimedia Computing and Service, ICIMCS 2010
Country/TerritoryChina
CityHarbin
Period30/12/1031/12/10

Keywords

  • Events detection
  • HCRF
  • Highlight
  • Soccer video

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