Bridging the semantic gap in sports video retrieval and summarization

Baoxin Li, James H. Errico, Hao Pan, Ibrahim Sezan

Research output: Contribution to journalReview article

35 Scopus citations

Abstract

One of the major challenges facing current media management systems and related applications is the so-called "semantic gap" between the rich meaning that a user desires and the shallowness of the content descriptions that are automatically extracted from the media. In this paper, we address the problem of bridging this gap in the sports domain. We propose a general framework for indexing and summarizing sports broadcast programs, with a high-level model of sports broadcast video using the concept of an event, defined according to domain-specific knowledge for different types of sports. Within this general framework, we develop automatic event detection algorithms that are based on automatic analysis of the visual and aural signals in the media. We have successfully applied the event detection algorithms to different types of sports including American football, baseball, Japanese sumo wrestling, and soccer. Event modeling and detection contribute to the reduction of the semantic gap by providing rudimentary semantic information obtained through media analysis. We further propose a novel approach, which makes use of independently generated rich textual metadata, to fill the gap completely through synchronization of the information-laden textual data with the basic event segments. We implemented an MPEG-7 compliant browsing system for semantic retrieval and summarization of sports video using the proposed algorithms.

Original languageEnglish (US)
Pages (from-to)393-424
Number of pages32
JournalJournal of Visual Communication and Image Representation
Volume15
Issue number3
DOIs
StatePublished - Sep 2004
Externally publishedYes

Keywords

  • Event detection
  • Semantic video analysis
  • Video summarization

ASJC Scopus subject areas

  • Signal Processing
  • Media Technology
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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