A rule-based video database system architecture

Abstract

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

An intelligent fuzzy object-oriented database framework for video database applications

“…Video databases are among those applications, which require powerful and flexible modeling and querying facilities. There are research efforts on utilizing knowledge-base systems or rule-based approach for video databases [32,33,34,35,48,49]. Among these, [33] defines spatial inference rules which allow to deduce heterogeneous spatial relations by using existing ones.…”

“…Among these, [33] defines spatial inference rules which allow to deduce heterogeneous spatial relations by using existing ones. In [34,49], an architecture for a video database application supporting spatio-temporal and semantic querying is proposed. The spatial relations are stored as Prolog facts in a knowledge base.…”

Automatic detection of salient objects and spatial relations in videos for a video database system

“…The knowledge-base of BilVideo contains a factbase and a comprehensive set of rules implemented in Prolog. The rules in the knowledge-base significantly reduce the number of facts that need to be stored for spatio-temporal querying of video data [10]. Query processor interacts with both the knowledge-base and object-relational database to respond to user queries that contain a combination of spatio-temporal, semantic, color, shape, and texture video queries.…”

Spatio-temporal querying in video databases

“…2 illustrates the segment tree generated from the map in Fig. 1 for the interval [1][2][3][4][5][6][7][8][9][10][11]. The set of numbers placed in a node denotes the identities of video objects and events that appeared in the entire frame-sequence associated with that node.…”

“…Although querying video databases is a newer concept, there have been several studies on querying the content of videos [1,8,11,12,13,15,16,17,18,19,20]. There exist mainly two different approaches for content-based query processing in video systems.…”