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Associating low-level features with semantic concepts using video objects and relevance feedback

Sav, Sorin and O'Connor, Noel E. and Smeaton, Alan F. and Murphy, Noel (2005) Associating low-level features with semantic concepts using video objects and relevance feedback. In: WIAMIS 2005 - 6th International Workshop on Image Analysis for Multimedia Interactive Services, 13-15 April 2005, Montreux, Switzerland.

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Abstract

The holy grail of multimedia indexing and retrieval is developing algorithms capable of imitating human abilities in distinguishing and recognising semantic concepts within the content, so that retrieval can be based on ”real world” concepts that come naturally to users. In this paper, we discuss an approach to using segmented video objects as the midlevel connection between low-level features and semantic concept description. In this paper, we consider a video object as a particular instance of a semantic concept and we model the semantic concept as an average representation of its instances. A system supporting object-based search through a test corpus is presented that allows matching presegmented objects based on automatically extracted lowlevel features. In the system, relevance feedback is employed to drive the learning of the semantic model during a regular search process.

Item Type:Conference or Workshop Item (Paper)
Event Type:Workshop
Refereed:Yes
Subjects:Computer Science > Digital video
Computer Science > Information retrieval
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Digital Video Processing (CDVP)
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Enterprise Ireland, European Commission IST-2000-32795
ID Code:403
Deposited On:02 Apr 2008 by DORAS Administrator. Last Modified 06 May 2010 10:03

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