BilVideo: A Video Database Management System
Ozgur Ulusoy, Ugur Gudukbay, Mehmet Emin Donderler, Ediz Saykol
by Bilkent University Multimedia Database GroupBilVideo WebClient can be accessed here.
BilVideo provides an integrated support for queries on spatio-temporal, semantic and low-level features (color, shape, and texture) on video data . A spatio-temporal query may contain any combination of directional, topological, object-appearance, 3D-relation, trajectory-projection and similarity-based object-trajectory conditions. BilVideo handles spatio-temporal queries using a knowledge-base, which consists of a fact-base and a comprehensive set of rules, while the queries on semantic and low-level features are handled by an object-relational database. The query processor interacts with both of the knowledge-base and object-relational database to respond to user queries that contain a combination of spatio-temporal, semantic, and low-level feature query conditions. Intermediate query results returned from these system components are integrated seamlessly by the query processor and sent to Web clients. Moreover, users can browse the video collection before giving complex and specific queries, and a text-based SQL-like query language is also available for users .
supports any application with query requirements on spatio-temporal, semantic
and low-level features on video data; therefore, it is application-independent.
However, it can easily be tailored according to the specific requirements of
such applications through the definition of external predicates supported by its
query language without much effort and any loss in performance.
Here, we present the Web-based visual query interface of BilVideo and its tools, Fact-Extractor and Video-Annotator, which are used to populate the facts-base and feature database of the system to support spatio-temporal and semantic video queries, respectively. Furthermore, an auxiliary module used to extract salient objects from video keyframes, called Object Extractor, is also presented .
Visual Query Interface: BilVideo can handle multiple requests
over the Internet through a graphical query interface developed as a Java
applet . The interface is composed of query specification windows for
different types of queries: spatial, trajectory, semantic, and low-level
features. Since video has a time dimension, these two types of primitive
queries can be combined with temporal predicates to query temporal
contents of videos.
This tool is used to extract spatio-temporal relations between video
objects and store them in the knowledge-base as facts. These facts
representing the extracted relations are used to query video data for
spatio-temporal conditions. The tool also extracts object trajectories and
3D-relations between objects of interest.
This tool is used to extract semantic data from video clips to be
stored in the feature database
to query video data for its semantic content. It provides some facilities
for viewing, updating and deleting semantic data that has already been
extracted from video clips and stored in the feature database. A demo of
video annotation through the Video-Annotator tool is available here.
Object Extractor: This tool is used to extract salient objects from video keyframes. It also facilitates the fact-extraction process automating the minimum bounding rectangle (MBR) specification of salient objects. A demo of the Object Extractor module is available here.
Şaykol, Web-based user interface for query specification in a video
database system, M.S. thesis, Dept. of Computer Engineering, Bilkent
University, Ankara, Turkey, Sept. 2001.
Şaykol, U. Güdükbay and Ö. Ulusoy, A semi-automatic object
extraction tool for querying in multimedia databases, MIS'01, Capri, Italy,
November 2001, pp. 11-20.
Şaykol, U. Güdükbay and Ö. Ulusoy, A histogram-based approach for
object-based query-by-shape-and-color in multi-media databases, submitted
journal paper and also available as BU-CE-0201, Bilkent Un., January 2002.
Ünel, M.E. Dönderler, Ö. Ulusoy, U. Güdükbay, An Efficient Query
Optimization Strategy for Spatio-Temporal Queries in Video Databases, to
appear in the J. of Sys. and Software.
Dönderler, E. Şaykol, U. Arslan, Ö. Ulusoy, U. Güdükbay, BilVideo:
Design and Implementation of a Video Database Management System,
to appear in Mult. Tools and Applications.
Dönderler, E. Şaykol, Ö. Ulusoy, U. Güdükbay, BilVideo:
A Video Database Management System, IEEE Multimedia, Vol.
10, No. 1, pp. 66-70, January/March 2003.
Dönderler, Ö. Ulusoy and U. Güdükbay, A rule-based video database system
architecture, Info. Sci., Vol. 143, No. 1-4, pp. 13-45, 2002.
M.E. Dönderler, Ö. Ulusoy and U. Güdükbay, Rule-based spatio-temporal query processing for video databases, VLDB Journal, Vol. 13, No. 1, pp. 86--103, January 2004.
U. Arslan, M.E. Dönderler, E. Şaykol, Ö Ulusoy, U. Güdükbay, A Semi-Automatic Semantic Annotation Tool for Video Databases, In SOFSEM 2002, Workshop on Multimedia Semantics, Milovy, Czech Republic, November 2002.
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