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A rule-based video annotation system

Dorado, A, Calic, J and Izquierdo, E (2004) A rule-based video annotation system Circuits and Systems for Video Technology, IEEE Transactions on, 14 (5). 622 - 633. ISSN 1051-8215

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Abstract

A generic system for automatic annotation of videos is introduced. The proposed approach is based on the premise that the rules needed to infer a set of high-level concepts from low-level descriptors cannot be defined a priori. Rather, knowledge embedded in the database and interaction with an expert user is exploited to enable system learning. Underpinning the system at the implementation level is preannotated data that dynamically creates signification links between a set of low-level features extracted directly from the video dataset and high-level semantic concepts defined in the lexicon. The lexicon may consist of words, icons, or any set of symbols that convey the meaning to the user. Thus, the lexicon is contingent on the user, application, time, and the entire context of the annotation process. The main system modules use fuzzy logic and rule mining techniques to approximate human-like reasoning. A rule-knowledge base is created on a small sample selected by the expert user during the learning phase. Using this rule-knowledge base, the system automatically assigns keywords from the lexicon to nonannotated video clips in the database. Using common low-level video representations, the system performance was assessed on a database containing hundreds of broadcasting videos. The experimental evaluation showed robust and high annotation accuracy. The system architecture offers straightforward expansion to relevance feedback and autonomous learning capabilities.

Item Type: Article
Additional Information: Copyright 2004 IEEE. 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 to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Uncontrolled Keywords: video clips, rule-based video annotation system, fuzzy set theory, knowledge based systems, lexicon, video extraction, data compression, system learning, semantic video annotation, semantic networks, rule mining techniques, video broadcasting, signification links, data mining techniques, learning systems, video signal processing, video dataset, inference mechanisms, low-level descriptors, rule-knowledge base, fuzzy logic, relevance feedback, multimedia databases, automatic video annotation, data mining, multimedia database
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Divisions: Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Communication Systems Research
Depositing User: Mr Adam Field
Date Deposited: 10 May 2012 13:20
Last Modified: 23 Sep 2013 19:24
URI: http://epubs.surrey.ac.uk/id/eprint/531495

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