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A Database Model for Querying Visual Surveillance Videos by Integrating Semantic and Low-Level Features

  • Ediz Şaykol
  • Uğur Güdükbay
  • Özgür Ulusoy
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3665)

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.

Keywords

Surveillance Video Salient Object Video Object Database Model Video Shot 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Ediz Şaykol
    • 1
  • Uğur Güdükbay
    • 1
  • Özgür Ulusoy
    • 1
  1. 1.Department of Computer EngineeringBilkent UniversityBilkent, AnkaraTurkey

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