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Semantic analysis of field sports video using a petri-net of audio-visual concepts

Liang, Bai and Lao, Songyang and Smeaton, Alan F. and O'Connor, Noel E. and Sadlier, David and Sinclair, David (2009) Semantic analysis of field sports video using a petri-net of audio-visual concepts. The Computer Journal, 52 (7). pp. 808-823. ISSN 0010-4620

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Abstract

The most common approach to automatic summarisation and highlight detection in sports video is to train an automatic classifier to detect semantic highlights based on occurrences of low-level features such as action replays, excited commentators or changes in a scoreboard. We propose an alternative approach based on the detection of perception concepts (PCs) and the construction of Petri-Nets which can be used for both semantic description and event detection within sports videos. Low-level algorithms for the detection of perception concepts using visual, aural and motion characteristics are proposed, and a series of Petri-Nets composed of perception concepts is formally defined to describe video content. We call this a Perception Concept Network-Petri Net (PCN-PN) model. Using PCN-PNs, personalized high-level semantic descriptions of video highlights can be facilitated and queries on high-level semantics can be achieved. A particular strength of this framework is that we can easily build semantic detectors based on PCN-PNs to search within sports videos and locate interesting events. Experimental results based on recorded sports video data across three types of sports games (soccer, basketball and rugby), and each from multiple broadcasters, are used to illustrate the potential of this framework.

Item Type:Article (Published)
Refereed:Yes
Uncontrolled Keywords:sports video; summarisation;
Subjects:Computer Science > Multimedia systems
Computer Science > Digital video
Computer Science > Algorithms
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > CLARITY: The Centre for Sensor Web Technologies
Publisher:Oxford University Press
Official URL:http://dx.doi.org/10.1093/comjnl/bxn058
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland
ID Code:15013
Deposited On:20 Nov 2009 16:31 by Alan F. Smeaton. Last Modified 20 Nov 2009 16:31

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