Tracking the invisible man: hidden-object detection for complex visual scene understanding

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

3 Citations (Scopus)


Reliable detection of objects of interest in complex visual scenes is of prime importance for video-surveillance applications. While most vision approaches deal with tracking visible or partially visible objects in single or multiple video streams, we propose a new approach to automatically detect all objects of interest being part of an analyzed scene, even those entirely hidden in a camera view whereas being present in the scene. For that, we have developed an innovative artificial-intelligence framework embedding a computer vision process fully integrating symbolic knowledge-based reasoning. Our system has been evaluated on standard datasets consisting of video streams with real-world objects evolving in cluttered, outdoor environment under difficult lighting conditions. Our proposed approach shows excellent performance both in detection accuracy and robustness, and outperforms state-of-the-art methods.
Original languageEnglish
Title of host publicationProceedings of the 8th International Conference on Agents and Artificial Intelligence
Subtitle of host publicationICAART
Number of pages7
ISBN (Print)9789897581724
Publication statusPublished - 26 Feb 2016
Externally publishedYes
EventInternational Conference on Agents and Artificial Intelligence - Rome, Italy
Duration: 24 Feb 201626 Feb 2016
Conference number: 8


ConferenceInternational Conference on Agents and Artificial Intelligence
Abbreviated titleICAART 2016
Internet address


  • Surveillance Application
  • Visual Scene Analysis
  • Automated Scene Understanding
  • Knowledge Representation
  • Spatio-temporal Visual Ontology
  • Symbolic Reasoning
  • Computer Vision
  • Pattern Recognition


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