A database model for querying visual surveillance videos by integrating semantic and low-level features

Date
2005
Advisor
Instructor
Source Title
Advances in Multimedia Information Systems
Print ISSN
1611-3349
Electronic ISSN
Publisher
Springer, Berlin, Heidelberg
Volume
3665
Issue
Pages
163 - 176
Language
English
Type
Conference Paper
Journal Title
Journal ISSN
Volume Title
Abstract

Automated visual surveillance has emerged as a trendy application domain in recent years. Many approaches have been developed on video processing and understanding. Content-based access to surveillance video has become a challenging research area. The results of a considerable amount of work dealing with automated access to visual surveillance have appeared in the literature. However, the event models and the content-based querying and retrieval components have significant gaps remaining unfilled. To narrow these gaps, we propose a database model for querying surveillance videos by integrating semantic and low-level features. In this paper, the initial design of the database model, the query types, and the specifications of its query language are presented. © Springer-Verlag Berlin Heidelberg 2005.

Course
Other identifiers
Book Title
Keywords
Information retrieval, Information technology, Mathematical models, Query languages, Semantics, Visual communication, Content-based querying, Database model, Surveillance video, Visual surveillance, Database systems
Citation