By Topic

Ontology-based surveillance video archive and retrieval system

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Ming Xue ; Department of Electronic Engineering, Shanghai Jiaotong University, Shanghai 200040, Shanghai, PRC ; Shibao Zheng ; Chongyang Zhang

Overwhelming amounts of surveillance video data are increasingly screwed up the pressure on efficient content-based retrieval and other applications. However, semantic gap exists between the low-level visual signal processing and high-level semantic understanding of the video event. In this paper, we propose an ontology-based content archive and retrieval framework for surveillance videos. Different from the generalized multimedia ontology framework, surveillance domain ontology is first designed as the content description schema, based on which video data is analyzed to form description files in Web Ontology Language (OWL). And then, a web-based semantic retrieval engine, which is compatible with the OWL query API, is developed to provide indexing service. Case study of “walking people” and “car parking” demonstrates that the proposed framework could generate OWL description of a video clip, and reversely locate the information efficiently.

Published in:

Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on

Date of Conference:

18-20 Oct. 2012