We propose a novel architecture for a video database system incorporating both spatio-temporal and semantic (keyword, event/activity and category-based) query facilities. The originality of our approach stems from the fact that we intend to provide full support for spatio-temporal, relative object-motion and similarity-based object-trajectory queries by a rule-based system utilizing a knowledge-base while using an object-relational database to answer semantic-based queries. Our method of extracting and modeling spatio-temporal relations is also a unique one such that we segment video clips into shots using spatial relationships between objects in video frames rather than applying a traditional scene detection algorithm. The technique we use is simple, yet novel and powerful in terms of effectiveness and user query satisfaction: video clips are segmented into shots whenever the current set of relations between objects changes and the video frames, where these changes occur, are chosen as keyframes. The directional, topological and third-dimension relations used for shots are those of the keyframes selected to represent the shots and this information is kept, along with frame numbers of the keyframes, in a knowledge-base as Prolog facts. The system has a comprehensive set of inference rules to reduce the number of facts stored in the knowledge-base because a considerable number of facts, which otherwise would have to be stored explicitly, can be derived by rules with some extra effort. © 2002 Elsevier Science Inc. All rights reserved

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 similaritybased object-trajectory conditions by a rule-based system built on a knowledge-base, while utilizing an objectrelational 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.

In our earlier work, we proposed an architecture for a Web-based video database management system (VDBMS) providing an integrated support for spatiotemporal and semantic queries. In this paper, we focus on the task of spatiotemporal query processing and also propose an SQL-like video query language that has the capability to handle a broad range of spatiotemporal queries. The language is rule-based in that it allows users to express spatial conditions in terms of Prologtype predicates. Spatiotemporal query processing is carried out in three main stages: query recognition, query decomposition, and query execution.

Message hierarchies in web discussion boards grow with new postings. Threads of messages evolve as new postings focus within or diverge from the original themes of the threads. Thus, just by investigating the subject headings or contents of earlier postings in a message thread, one may not be able to guess the contents of the later postings. The resulting navigation problem is further compounded for blind users who need the help of a screen reader program that can provide only a linear representation of the content. We see that, in order to overcome the navigation obstacle for blind as well as sighted users, it is essential to develop techniques that help identify how the content of a discussion board grows through generalizations and specializations of topics. This knowledge can be used in segmenting the content in coherent units and guiding the users through segments relevant to their navigational goals. Our experimental results showed that the segmentation algorithm described in this paper provides up to 80 − 85% success rate in labeling messages. The algorithm is being deployed in a software system to reduce the navigational load of blind students in accessing web-based electronic course materials; however, we note that the techniques are equally applicable for developing web indexing and summarization tools for users with sight.

No abstract