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Journal ArticleDOI

Distributed and reactive query planning in R-MAGIC: an agent-based multimedia retrieval system

TL;DR: 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.
Citations
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Book ChapterDOI
01 Jan 2007
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.
Abstract: An ontology designed for multimedia applications should enable integration of the conceptual and media spaces. We present M-OWL, a new ontology language, that supports this capability. M-OWL supports explicit definition of media properties for the concepts. The language has been defined as an extension of OWL, the standard ontology language for the web. We have proposed a new Bayesian Network based probabilistic reasoning framework with M-OWL for semantic interpretation of multimedia data. We have also proposed a new model for ontology integration, based on the similarity of the concepts in the media domain. It can be used to integrate several multimedia and traditional ontologies.

33 citations


Cites background from "Distributed and reactive query plan..."

  • ...Selection of a sufficient and computationally optimal subset of observation nodes through a distributed planning process has been discussed in [ 51 ]....

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Journal ArticleDOI
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.
Abstract: Several multimedia applications need to reason with concepts and their media properties in specific domain contexts. Media properties of concepts exhibit some unique characteristics that cannot be dealt with conceptual modeling schemes followed in the existing ontology representation and reasoning schemes. We have proposed a new perceptual modeling technique for reasoning with media properties observed in multimedia instances and the latent concepts. Our knowledge representation scheme uses a causal model of the world where concepts manifest in media properties with uncertainties. We introduce a probabilistic reasoning scheme for belief propagation across domain concepts through observation of media properties. In order to support the perceptual modeling and reasoning paradigm, we propose a new ontology language, Multimedia Web Ontology Language (MOWL). Our primary contribution in this article is to establish the need for the new ontology language and to introduce the semantics of its novel language constructs. We establish the generality of our approach with two disperate knowledge-intensive applications involving reasoning with media properties of concepts.

27 citations

Proceedings ArticleDOI
31 Aug 2005
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.
Abstract: In this paper, we propose a scheme for accessing document images using ontology. We make use of an extension of OWL (ontology language for Web) to allow encoding of ontologies for document images. We experimentally demonstrate that reasoning with the concepts defined in ontology and their observation models provide a mechanism to support conceptual querying and automated hyperlinking of document images.

10 citations


Cites methods from "Distributed and reactive query plan..."

  • ...Conceptual Querying of documents is done by forming an Observation Model (OM) [4] for the concept which is to be queried....

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Book ChapterDOI
20 Dec 2005
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.
Abstract: This paper present a novel framework for formal specification of spatio-temporal relations between media objects using fuzzy membership. We have illustrated its use in multimedia ontologies and have described a reasoning framework for creating media based descriptions of concepts.

8 citations

References
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Journal ArticleDOI
TL;DR: A near-real-time computer system that can locate and track a subject's head, and then recognize the person by comparing characteristics of the face to those of known individuals, and that is easy to implement using a neural network architecture.
Abstract: We have developed a near-real-time computer system that can locate and track a subject's head, and then recognize the person by comparing characteristics of the face to those of known individuals. The computational approach taken in this system is motivated by both physiology and information theory, as well as by the practical requirements of near-real-time performance and accuracy. Our approach treats the face recognition problem as an intrinsically two-dimensional (2-D) recognition problem rather than requiring recovery of three-dimensional geometry, taking advantage of the fact that faces are normally upright and thus may be described by a small set of 2-D characteristic views. The system functions by projecting face images onto a feature space that spans the significant variations among known face images. The significant features are known as "eigenfaces," because they are the eigenvectors (principal components) of the set of faces; they do not necessarily correspond to features such as eyes, ears, and noses. The projection operation characterizes an individual face by a weighted sum of the eigenface features, and so to recognize a particular face it is necessary only to compare these weights to those of known individuals. Some particular advantages of our approach are that it provides for the ability to learn and later recognize new faces in an unsupervised manner, and that it is easy to implement using a neural network architecture.

14,562 citations

Journal ArticleDOI
TL;DR: In this paper, color histograms of multicolored objects provide a robust, efficient cue for indexing into a large database of models, and they can differentiate among a large number of objects.
Abstract: Computer vision is moving into a new era in which the aim is to develop visual skills for robots that allow them to interact with a dynamic, unconstrained environment. To achieve this aim, new kinds of vision algorithms need to be developed which run in real time and subserve the robot's goals. Two fundamental goals are determining the identity of an object with a known location, and determining the location of a known object. Color can be successfully used for both tasks. This dissertation demonstrates that color histograms of multicolored objects provide a robust, efficient cue for indexing into a large database of models. It shows that color histograms are stable object representations in the presence of occlusion and over change in view, and that they can differentiate among a large number of objects. For solving the identification problem, it introduces a technique called Histogram Intersection, which matches model and image histograms and a fast incremental version of Histogram Intersection which allows real-time indexing into a large database of stored models. It demonstrates techniques for dealing with crowded scenes and with models with similar color signatures. For solving the location problem it introduces an algorithm called Histogram Backprojection which performs this task efficiently in crowded scenes.

5,672 citations

Journal ArticleDOI
TL;DR: The Query by Image Content (QBIC) system as discussed by the authors allows queries on large image and video databases based on example images, user-constructed sketches and drawings, selected color and texture patterns, camera and object motion, and other graphical information.
Abstract: Research on ways to extend and improve query methods for image databases is widespread. We have developed the QBIC (Query by Image Content) system to explore content-based retrieval methods. QBIC allows queries on large image and video databases based on example images, user-constructed sketches and drawings, selected color and texture patterns, camera and object motion, and other graphical information. Two key properties of QBIC are (1) its use of image and video content-computable properties of color, texture, shape and motion of images, videos and their objects-in the queries, and (2) its graphical query language, in which queries are posed by drawing, selecting and other graphical means. This article describes the QBIC system and demonstrates its query capabilities. QBIC technology is part of several IBM products. >

3,957 citations

Journal ArticleDOI
TL;DR: In this article, the contract net protocol has been developed to specify problem-solving communication and control for nodes in a distributed problem solver, where task distribution is affected by a negotiation process, a discussion carried on between nodes with tasks to be executed and nodes that may be able to execute those tasks.
Abstract: The contract net protocol has been developed to specify problem-solving communication and control for nodes in a distributed problem solver. Task distribution is affected by a negotiation process, a discussion carried on between nodes with tasks to be executed and nodes that may be able to execute those tasks.

3,612 citations

Book ChapterDOI
12 Aug 1996
TL;DR: This work proposes a formal definition of an autonomous agent which clearly distinguishes a software agent from just any program, and offers the beginnings of a natural kinds taxonomy of autonomous agents.
Abstract: The advent of software agents gave rise to much discussion of just what such an agent is, and of how they differ from programs in general. Here we propose a formal definition of an autonomous agent which clearly distinguishes a software agent from just any program. We also offer the beginnings of a natural kinds taxonomy of autonomous agents, and discuss possibilities for further classification. Finally, we discuss subagents and multiagent systems.

2,504 citations


Additional excerpts

  • ...Index Terms—Reactive planning, distributed planning, multimedia retrieval, distributed retrieval, agent-based systems....

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