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

  • Authors:

  • Tarkan Sevilmiş;Muhammet Baştan;Uğur Güdükbay;Özgür Ulusoy

  • Affiliations:

  • Department of Computer Engineering, Bilkent University, Bilkent, 06800 Ankara, Turkey;Department of Computer Engineering, Bilkent University, Bilkent, 06800 Ankara, Turkey;Department of Computer Engineering, Bilkent University, Bilkent, 06800 Ankara, Turkey;Department of Computer Engineering, Bilkent University, Bilkent, 06800 Ankara, Turkey

  • Venue:
  • Image and Vision Computing
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

Abstract

Multimedia databases have gained popularity due to rapidly growing quantities of multimedia data and the need to perform efficient indexing, retrieval and analysis of this data. One downside of multimedia databases is the necessity to process the data for feature extraction and labeling prior to storage and querying. Huge amount of data makes it impossible to complete this task manually. We propose a tool for the automatic detection and tracking of salient objects, and derivation of spatio-temporal relations between them in video. Our system aims to reduce the work for manual selection and labeling of objects significantly by detecting and tracking the salient objects, and hence, requiring to enter the label for each object only once within each shot instead of specifying the labels for each object in every frame they appear. This is also required as a first step in a fully-automatic video database management system in which the labeling should also be done automatically. The proposed framework covers a scalable architecture for video processing and stages of shot boundary detection, salient object detection and tracking, and knowledge-base construction for effective spatio-temporal object querying.