Robust TV Commercial Detection Based on Audiovisual Features

Shih Hung Lee*, Chia H. Yeh, C. C. Jay Kuo

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review


A robust TV commercial detection system is proposed in this research. Even though several methods were investigated to address the TV commercial detection problem and interesting results were obtained before, most previous work focuses on features within a short temporal window. These methods are suitable for on-line detection, but often result in higher false alarm rates as a trade-off. To reduce the false alarm rate, we explore audiovisual features in a larger temporal window. Specifically, we group shots into scenes using audio data processing, and then obtain features that are related to commercial characteristics from scenes. Experimental results are given to demonstrate the effectiveness of the proposed system.

Original languageEnglish
Pages (from-to)147-158
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
Publication statusPublished - 2003
Externally publishedYes
EventPROCEEDINGS OF SPIE SPIE - The International Society for Optical Engineering: Visual Information Processing XII - Orlando, FL, United States
Duration: 2003 Apr 212003 Apr 21


  • Audio Classification
  • Audiovisual Analysis
  • Commercial Break
  • Content Analysis

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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