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Video semantic content analysis based on ontology

Bai, Liang and Lao, Songyang and Jones, Gareth J.F. and Smeaton, Alan F. (2007) Video semantic content analysis based on ontology. In: IMVIP 2007 - 11th International Machine Vision and Image Processing Conference, 5-7 September 2007, Maynooth, Ireland.

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Abstract

The rapid increase in the available amount of video data is creating a growing demand for efficient methods for understanding and managing it at the semantic level. New multimedia standards, such as MPEG-4 and MPEG-7, provide the basic functionalities in order to manipulate and transmit objects and metadata. But importantly, most of the content of video data at a semantic level is out of the scope of the standards. In this paper, a video semantic content analysis framework based on ontology is presented. Domain ontology is used to define high level semantic concepts and their relations in the context of the examined domain. And low-level features (e.g. visual and aural) and video content analysis algorithms are integrated into the ontology to enrich video semantic analysis. OWL is used for the ontology description. Rules in Description Logic are defined to describe how features and algorithms for video analysis should be applied according to different perception content and low-level features. Temporal Description Logic is used to describe the semantic events, and a reasoning algorithm is proposed for events detection. The proposed framework is demonstrated in a soccer video domain and shows promising results.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Subjects:Computer Science > Digital video
Computer Science > Information retrieval
Computer Science > Image processing
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Digital Video Processing (CDVP)
Publisher:Institute of Electrical and Electronics Engineers
Official URL:http://dx.doi.org/10.1109/IMVIP.2007.44
Copyright Information:Copyright © 2007 IEEE. Reprinted from IMVIP 2007 - Proceedings of the 11th International Machine Vision and Image Processing Conference. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Dublin City University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
Funders:Science Foundation Ireland, SFI 03/IN.3/I361, National High Technology Development 863 Program of China, National Natural Science Foundation of China
ID Code:218
Deposited On:05 Mar 2008 by DORAS Administrator. Last Modified 05 May 2010 10:42

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