Multimedia Query Language Research Articles

GMQL: A graphical multimedia query language

The rapid increase of multimedia data makes multimedia query more and more important. To better satisfy users’ query requirements, developing a functional multimedia query language is becoming a promising and interesting task. In this paper, we propose a graphical multimedia query language called GMQL, which is developed based on a semi-structured data organization model. In GMQL, we combine the advantages of graphs and texts, making the query language much clear, easy to use and with powerful expressiveness. In this paper, we first present the notations and basic capabilities of GMQL by query examples. Second, we discuss the GMQL query processing techniques. Last, we evaluate and analyze our multimedia query language through the comparison with other existing multimedia query languages. The evaluation results show that, GMQL has powerful expressiveness, and thus is much applicable for multimedia information retrieval.

Hierarchical image modeling for object-based media retrieval

Images are more structurally complex than the data stored in the traditional DBMSs. Many systems perform media retrieval based on image feature matching; the fact that images have structures is ignored. On the other hand, we view images as compound objects containing many component objects. Each component object corresponds to a region(s) that is a visually and semantically meaningful entity (e.g. car, man, etc.). As images/objects truly have hierarchical structures and have both visual and semantics properties, we argue that image retrieval using either semantics and image matching alone is insufficient. In this paper, we introduce a hierarchical structure for image modeling to support image retrieval using combinations of semantic expressions and visual examples at both the whole image and object levels. We give formal definitions of a multimedia query language and a system implementation based on this image modeling. We also address associated query processing issues and discuss the portability and extendibility of our approach.

WAG: WEB-AT-A-GLANCE

The Internet revolution has made an enormous quantity of information available to a disparate variety of people. The amount of information, the typical access modality (that is, browsing), and the rapid growth of the Net, force the user, while searching for the information of interest, to dip into multiple sources, in a labyrinth of millions of links. Web-at-A-Glance (WAG) is a system allowing the user to query (instead of browsing) the Web. WAG performs this ambitious task by constructing a personalized database, pertinent to the user's interests. The system semi-automatically gleans the most relevant information from a Web site or several Web sites, stores them into a database cooperatively designed with the user, and allows her/him to query such a database through a visual interface equipped with a powerful multimedia query language. This paper presents the design philosophy, the architecture and the core of the WAG system. A prototype WAG is being implemented to test the feasibility of the proposed approach.

An Approach to a Content-Based Retrieval ofMultimedia Data

This paper presents a data model tailored for multimedia data representation, along with the main characteristics of a Multimedia Query Language that exploits the features of the proposed model. The model addresses data presentation, manipulation and content-based retrieval. It consists of three parts: a Multimedia Description Model, which provides a structural view of raw multimedia data, a Multimedia Presentation Model, and a Multimedia Interpretation Model which allows semantic information to be associated with multimedia data. The paper focuses on the structuring of a multimedia data model which provides support for content-based retrieval of multimedia data. The Query Language is an extension of a traditional query language which allows restrictions to be expressed on features, concepts, and the structural aspects of the objects of multimedia data and the formulation of queries with imprecise conditions. The result of a query is an approximate set of database objects which partially match such a query.