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Title
Abstract
Introduction
Ontology for Multimedia Data Interpretation
Discussions
Product Recommendation for Featurerich Commodities
Conclusions
References

Ontology For Multimedia Applications

Profile image of Hiranmay GhoshHiranmay Ghosh

Abstract

This paper provides an overview of the contents of a tutorial on the subject by one of the authors at WI-2013 Conference. The domination of multimedia contents on the web in recent times has motivated research in their semantic analysis. This tutorial aims to provide a critical overview of the technology, and focuses on application of ontologies for multimedia applications. It establishes the need for a fundamentally different approach for a representation and reasoning scheme with ontologies for semantic interpretation of multimedia contents. It introduces a new ontology representation scheme that enables reasoning with uncertain media properties of concepts in a domain context and a language "Multimedia Web Ontology Language" (MOWL) to support the representation scheme. We discuss the approaches to semantic modeling and ontology learning with specific reference to the probabilistic framework of MOWL. We present a couple of illustrative application examples. Further, we discuss the issues of distributed multimedia information systems and how the new ontology representation scheme can create semantic interoperability across heterogeneous multimedia data sources.

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COMM: designing a well-founded multimedia ontology for the web
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Semantic descriptions of non-textual media available on the web can be used to facilitate retrieval and presentation of media assets and documents containing them. While technologies for multimedia semantic descriptions already exist, there is as yet no formal description of a high quality multimedia ontology that is compatible with existing (semantic) web technologies. We explain the complexity of the problem using an annotation scenario. We then derive a number of requirements for specifying a formal multimedia ontology before we present the developed ontology, COMM, and evaluate it with respect to our requirements. We provide an API for generating multimedia annotations that conform to COMM.

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Semantic descriptions of non-textual media available on the web can be used to facilitate retrieval and presentation of media assets and documents containing them. While technologies for multimedia semantic descriptions already exist, there is as yet no formal description of a high quality multimedia ontology that is compatible with existing (semantic) web technologies. We explain the complexity of the problem using an annotation scenario. We then derive a number of requirements for specifying a formal multimedia ontology, including: compatibility with MPEG-7, embedding in foundational ontologies, and modularisation including separation of document structure from domain knowledge. We then present the developed ontology and discuss it with respect to our requirements.

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Multimedia content and descriptor ontologies–final version
Giorgos Stoilos

Abstract (for dissemination) This deliverable presents the final outcome of Task 3.1 “Multimedia content and descriptor ontologies” in the BOEMIE project. Two ontologies, namely the Multimedia Content Ontology (MCO) and the Multimedia Descriptor Ontology (MDO) have been developed aiming to support the effective extraction of multimedia content semantics through the formal representation of media related knowledge. In the first year of the project, the initial versions of the ontologies were released.

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Enhancing the semantic interoperability of multimedia through a core ontology
Jane Hunter

IEEE Transactions on Circuits and Systems for Video Technology, 2003

A core ontology is one of the key building blocks necessary to enable the integration of information from diverse multimedia sources. A complete and extensible ontology that expresses the basic concepts that are common across a variety of domains and media types and that can provide the basis for specialization into domain-specific concepts and vocabularies, is essential for well-defined mappings between domain-specific knowledge representations (i.e., metadata vocabularies) and the subsequent building of a variety of services such as cross-domain searching, tracking, browsing, data mining and knowledge acquisition. As more and more communities develop metadata application profiles which combine terms from multiple vocabularies (e.g., Dublin Core, MPEG-7, MPEG-21, CIDOC/CRM, FGDC, IMS) such a core ontology will provide a common understanding of the basic entities and relationships which is essential for semantic interoperability and the development of additional services based on deductive inferencing. In this paper we first propose such a core ontology (the ABC model) which was developed in response to a need to integrate information from multiple genres of multimedia content within digital libraries and archives. Although the MPEG-21 RDD was influenced by the ABC model and is based on a model extremely similar to ABC, we believe that it is important to define a separate and domain-independent top-level extensible ontology for scenarios in which either MPEG-21 is irrelevant or to enable the attachment of ontologies from communities external to MPEG, for example, the museum domain (CIDOC/CRM) or the bio-medical domain (ON9.3). We then evaluate the ABC model's ability to mediate and integrate between multimedia metadata vocabularies by illustrating how it can provide the foundation to facilitate semantic interoperability between MPEG-7, MPEG-21 and other domain-specific metadata vocabularies. By expressing the semantics of both MPEG-7 and MPEG-21 metadata terms in RDF Schema/DAML+OIL (and eventually the Web Ontology Language (OWL)) and attaching the MPEG-7 and MPEG-21 class and property hierarchies to the appropriate top-level classes and properties of the ABC model, we have defined a single distributed machine-understandable ontology. The resulting distributed machineprocessable ontology provides semantic knowledge which is non-existent within declarative XML schemas or XML-encoded metadata descriptions. Finally, in order to illustrate how such an ontology will contribute to the interoperability of data and services across the entire multimedia content delivery chain, we describe a number of valuable services which have been developed or could potentially be developed using the resulting merged ontologies.

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OntoMedia: An ontology for the representation of heterogeneous media
David Millard

2005

With the emergence of the Semantic Web, a shared vocabulary is necessary to annotate the vast collection of heterogeneous media already in existence. The OntoMedia ontology aims to provide a meaningful set of relationships which may enable this process, while being suited to mapping and extension. In this paper we outline the salient features of our ontology as well as initial applications and comparisons to existing technologies.

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Semantic Modeling of Digital Multimedia
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- The requirement for a commonly accepted efficient mapping between multimedia metadata standards and semantic web-ontology standards is a major issue recognized by semantic multimedia research community. Though there have been several attempts to translate MPEG-7 ...

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Semantic representation of multimedia content: Knowledge representation and semantic indexing
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In this paper we present a framework for unified, personalized access to heterogeneous multimedia content in distributed repositories. Focusing on semantic analysis of multimedia documents, metadata, user queries and user profiles, it contributes to the bridging of the gap between the semantic nature of user queries and raw multimedia documents. The proposed approach utilizes as input visual content analysis results, as well as analyzes and exploits associated textual annotation, in order to extract the underlying semantics, construct a semantic index and classify documents to topics, based on a unified knowledge and semantics representation model. It may then accept user queries, and, carrying out semantic interpretation and expansion, retrieve documents from the index and rank them according to user preferences, similarly to text retrieval. All processes are based on a novel semantic processing methodology, employing fuzzy algebra and principles of taxonomic knowledge representation. The first part of this work presented in this paper deals with data and knowledge models, manipulation of multimedia content annotations and semantic indexing, while the second part will continue on the use of the extracted semantic information for personalized retrieval.

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Combined Domain Specific and Multimedia Ontologies for Image Understanding
Thanos Athanasiadis

Knowledge representation and annotation of multimedia documents typically have been pursued in two different directions. Previous approaches have focused either on low level descriptors, such as dominant color, or on the content dimension and corresponding manual annotations, such as person or vehicle. In this paper, we present a knowledge infrastructure to bridge the gap between the two directions. Ontologies are being extended and enriched to include low-level audiovisual features and descriptors. Additionally, a tool for linking low-level MPEG-7 visual descriptions to ontologies and annotations has been developed. In this way, we construct ontologies that include prototypical instances of domain concepts together with a formal specification of the corresponding visual descriptors. Thus, we combine high-level domain concepts and low-level multimedia descriptions, enabling for new media content analysis.

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