Technicolor challenge: An event classification framework by probabilistic context modeling of multimodal features

Hsuan Sheng Chen*, W. J. Tsai

*Corresponding author for this work

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

Abstract

Semantic high-level event recognition of videos is one of most interesting issues for multimedia searching and indexing. Since high-level events are usually domain-specific, a generic framework which can adapt itself to new domains without or with a few modifications is needed. To this end, this paper presents a generic framework for video event classification using temporal context of interval-based multimodal features. In the framework, a co-occurrence symbol transformation method is proposed to explore full temporal relations among multiple modalities in probabilistic HMM event classification. The results of our experiments on baseball video event classification demonstrate the superiority of the proposed approach.

Original languageEnglish
Title of host publicationMM 2012 - Proceedings of the 20th ACM International Conference on Multimedia
Pages1353-1354
Number of pages2
DOIs
StatePublished - 26 Dec 2012
Event20th ACM International Conference on Multimedia, MM 2012 - Nara, Japan
Duration: 29 Oct 20122 Nov 2012

Publication series

NameMM 2012 - Proceedings of the 20th ACM International Conference on Multimedia

Conference

Conference20th ACM International Conference on Multimedia, MM 2012
CountryJapan
CityNara
Period29/10/122/11/12

Keywords

  • co-occurrence symbol
  • event classification
  • HMM
  • interval-based representation
  • multimodal feature
  • multivariate temporal data classification
  • probabilistic modeling
  • semantics
  • temporal relation

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