Detecting hidden objects using efficient spatio-temporal knowledge representation

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

Detecting visible as well as invisible objects of interest in real-world scenes is crucial in new-generation video-surveillance. For this purpose, we design a fully intelligent system incorporating semantic, symbolic, and grounded information. In particular, we conceptualize temporal representations we use together with spatial and visual information in our multi-view tracking system. It uses them for automated reasoning and induction of knowledge about the multiple views of the studied scene, in order to automatically detect salient or hidden objects of interest. Tests on standard datasets demonstrated the efficiency and accuracy of our proposed approach.
Original languageEnglish
Title of host publicationAgents and Artificial Intelligence
Subtitle of host publicationICAART 2016
EditorsJ. van den Herik, J. Filipe
PublisherSpringer
Pages302-313
Number of pages12
Volume10162
ISBN (Electronic)978-3-319-53354-4
ISBN (Print)978-3-319-53353-7
DOIs
Publication statusPublished - 2017
Externally publishedYes

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume10162

Keywords

  • Surveillance application
  • Visual scene analysis
  • Automated scene understanding
  • Knowledge representation
  • Spatio-temporal visual ontology
  • Symbolic reasoning
  • Computer vision
  • Pattern recognition

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