10 research outputs found

    Content-based Video Retrieval

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    STRG-QL: Spatio-Temporal Region Graph Query Language for Video Databases

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    Copyright 2008 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.In this paper, we present a new graph-based query language and its query processing for a Graph-based Video Database Management System (GVDBMS). Although extensive researches have proposed various query languages for video databases, most of them have the limitation in handling general-purpose video queries. Each method can handle specific data model, query type or application. In order to develop a general-purpose video query language, we first produce Spatio-Temporal Region Graph (STRG) for each video, which represents spatial and temporal information of video objects. An STRG data model is generated from the STRG by exploiting object-oriented model. Based on the STRG data model, we propose a new graph-based query language named STRG-QL, which supports various types of video query. To process the proposed STRG-QL, we introduce a rule-based query optimization that considers the characteristics of video data, i.e., the hierarchical correlations among video segments. The results of our extensive experimental study show that the proposed STRG-QL is promising in terms of accuracy and cost.http://dx.doi.org/10.1117/12.76553

    A Database Approach for Modeling and Querying Video Data

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    Indexing video data is essential for providing content based access. In this paper, we consider how database technology can offer an integrated framework for modeling and querying video data. As many concerns in video (e.g., modeling and querying) are also found in databases, databases provide an interesting angle to attack many of the problems. From a video applications perspective, database systems provide a nice basis for future video systems. More generally, database research will provide solutions to many video issues even if these are partial or fragmented. From a database perspective, video applications provide beautiful challenges. Next generation database systems will need to provide support for multimedia data (e.g., image, video, audio). These data types require new techniques for their management (i.e., storing, modeling, querying, etc.). Hence new solutions are significant. This paper develops a data model and a rule-based query language for video content based indexing and retrieval. The data model is designed around the object and constraint paradigms. A video sequence is split into a set of fragments. Each fragment can be analyzed to extract the information (symbolic descriptions) of interest that can be put into a database. This database can then be searched to find information of interest. Two types of information are considered: (1) the entities (objects) of interest in the domain of a video sequence, (2) video frames which contain these entities. To represent these information, our data model allows facts as well as objects and constraints. We present a declarative, rule-based, constraint query language that can be used to infer relationships about information represented in the model. The language has a clear declarative and operational semantics. This work is a major revision and a consolidation of [12, 13].This is an extended version of the article in: 15th International Conference on Data Engineering, Sydney, Australia, 1999

    BilVideo: Design and implementation of a video database management system

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    With the advances in information technology, the amount of multimedia data captured, produced, and stored is increasing rapidly. As a consequence, multimedia content is widely used for many applications in today's world, and hence, a need for organizing this data, and accessing it from repositories with vast amount of information has been a driving stimulus both commercially and academically. In compliance with this inevitable trend, first image and especially later video database management systems have attracted a great deal of attention, since traditional database systems are designed to deal with alphanumeric information only, thereby not being suitable for multimedia data. In this paper, a prototype video database management system, which we call BilVideo, is introduced. The system architecture of BilVideo is original in that it provides full support for spatio-temporal queries that contain any combination of spatial, temporal, object-appearance, external-predicate, trajectory-projection, and similarity-based object-trajectory conditions by a rule-based system built on a knowledge-base, while utilizing an object-relational database to respond to semantic (keyword, event/activity, and category-based), color, shape, and texture queries. The parts of BilVideo (Fact-Extractor, Video-Annotator, its Web-based visual query interface, and its SQL-like textual query language) are presented, as well. Moreover, our query processing strategy is also briefly explained. © 2005 Springer Science + Business Media, Inc

    Multi-level Video Filtering Using Non-textual Contents

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