Journal ArticleDOI
Distributed and reactive query planning in R-MAGIC: an agent-based multimedia retrieval system
Hiranmay Ghosh,Santanu Chaudhury +1 more
TLDR
A prototype implementation of a cooperative agent-based multimedia retrieval architecture that integrates a set of dissimilar collections of multimedia data on Indian cultural heritage and a comparison of the retrieval results with some existing Internet search tools proves the effectiveness of the architecture.Abstract:
We present the planning scheme for a cooperative agent-based multimedia retrieval architecture that integrates a heterogeneous set of repositories into a coherent information system. The agents in the system collaborate in context of a conceptual query to formulate unique retrieval strategies for the different collections. The retrieval plan makes need-based use of independent content analysis tools available on the network. The retrieval strategies for the repositories so formulated satisfy the specified constraints on quality of results and the response time requirements. The retrieval plan is reactively updated based on the retrieval performance at the individual repositories. We present some experimental results to show the effectiveness of the planning scheme for repositories with different characteristics and the scalability of the architecture. We present a prototype implementation of this architecture that integrates a set of dissimilar collections of multimedia data on Indian cultural heritage. A comparison of the retrieval results with some existing Internet search tools proves the effectiveness of the architecture.read more
Citations
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Book ChapterDOI
Ontology Specification and Integration for Multimedia Applications
TL;DR: A new Bayesian Network based probabilistic reasoning framework with M-OWL for semantic interpretation of multimedia data and a new model for ontology integration, based on the similarity of the concepts in the media domain are proposed.
Journal ArticleDOI
MOWL: An ontology representation language for web-based multimedia applications
TL;DR: A new perceptual modeling technique for reasoning with media properties observed in multimedia instances and the latent concepts is proposed, and a probabilistic reasoning scheme for belief propagation across domain concepts through observation of media properties is introduced.
Proceedings ArticleDOI
Ontology guided access to document images
TL;DR: This paper makes use of an extension of OWL (ontology language for Web) to allow encoding of ontologies for document images to support conceptual querying and automated hyperlinking of document images.
Book ChapterDOI
Specifying spatio temporal relations for multimedia ontologies
TL;DR: A novel framework for formal specification of spatio-temporal relations between media objects using fuzzy membership and its use in multimedia ontologies and a reasoning framework for creating media based descriptions of concepts are presented.
References
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Book
Information Modelling and Knowledge Bases
TL;DR: The topics of the articles cover a wide variety of themes in the domain of information modelling, design and specification of information systems and knowledge bases, ranging from foundations and theories to systems construction and application studies.
Proceedings ArticleDOI
Illumination-invariant color object recognition via compressed chromaticity histograms of color-channel-normalized images
Mark S. Drew,Jie Wei,Ze-Nian Li +2 more
TL;DR: The seminal method of Swain and Ballard to discount changing illumination is extended, based on the first stage of the simplest color indexing method, which uses angular invariants between color image and edge image channels.
Journal ArticleDOI
AND/OR graph heuristic search methods
A. Mahanti,Amitava Bagchi +1 more
TL;DR: Two new marking algorithms for AND/OR graphs called CF and CS are presented and it is proved that CF can be followed by CS to get optimal solutions, provided the sumcost criterion is used and the first discriminant equals the second.
Journal ArticleDOI
Semantic indexing of multimedia documents
TL;DR: This work bases the first approach on a finite-state machine using low-level motion indices extracted from an MPEG compressed bitstream and innovatively performs semantic indexing through Hidden Markov Models.