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Detecting Hidden Objects Using Efficient Spatio-Temporal Knowledge Representation

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Agents and Artificial Intelligence (ICAART 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10162))

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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.

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Author information

Authors and Affiliations

  1. University of Gloucestershire, Cheltenham, UK

    Joanna Isabelle Olszewska

Authors
  1. Joanna Isabelle Olszewska
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Correspondence to Joanna Isabelle Olszewska .

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Editors and Affiliations

  1. Leiden University, Leiden, The Netherlands

    Jaap van den Herik

  2. Polytechnic Institute of Setúbal/INSTICC, Setúbal, Portugal

    Joaquim Filipe

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Olszewska, J.I. (2017). Detecting Hidden Objects Using Efficient Spatio-Temporal Knowledge Representation. In: van den Herik, J., Filipe, J. (eds) Agents and Artificial Intelligence. ICAART 2016. Lecture Notes in Computer Science(), vol 10162. Springer, Cham. https://doi.org/10.1007/978-3-319-53354-4_17

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  • DOI: https://doi.org/10.1007/978-3-319-53354-4_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-53353-7

  • Online ISBN: 978-3-319-53354-4

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