Paper
10 January 2003 Bridging the semantic gap in sports
Baoxin Li, James Errico, Hao Pan, M. Ibrahim Sezan
Author Affiliations +
Proceedings Volume 5021, Storage and Retrieval for Media Databases 2003; (2003) https://doi.org/10.1117/12.476261
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States
Abstract
One of the major challenges facing current media management systems and the 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. The framework is based on 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. An MPEG-7 compliant prototype browsing system has been implemented to demonstrate semantic retrieval and summarization of sports video.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Baoxin Li, James Errico, Hao Pan, and M. Ibrahim Sezan "Bridging the semantic gap in sports", Proc. SPIE 5021, Storage and Retrieval for Media Databases 2003, (10 January 2003); https://doi.org/10.1117/12.476261
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CITATIONS
Cited by 10 scholarly publications.
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KEYWORDS
Video

Optical character recognition

Detection and tracking algorithms

Algorithm development

Computer programming

Composites

Semantic video

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