A novel decentralised system architecture for multi-camera target tracking

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Abstract

Target tracking in a multi-camera system is an active and challenging research that in many systems requires video synchronisation and knowledge of the camera set-up and layout. In this paper a highly flexible, modular and decentralised system architecture is presented for multi-camera target tracking with relaxed synchronisation constraints among camera views. Moreover, the system does not rely on positional information to handle camera hand-off events. As a practical application, the system itself can, at any time, automatically select the best target view available, to implicitly solve occlusion. Further, to validate the proposed architecture, an extension to a multi-camera environment of the colour-based IMS-SWAD tracker is used. The experimental results show that the tracker can successfully track a chosen target in multiple views, in both indoor and outdoor environments, with non-overlapping and overlapping camera views.
Original languageEnglish
Title of host publicationAdvanced Concepts for Intelligent Vision Systems (ACIVS2016)
Place of PublicationBerlin
Pages92-104
Number of pages13
Volume10016
DOIs
Publication statusPublished - 21 Oct 2016
EventAdvanced Concepts for Intelligent Vision Systems 2016 - Patria Palace Hotel, Lecce, Italy
Duration: 24 Oct 201627 Oct 2016
http://acivs.org/acivs2016/

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
ISSN (Print)0302-9743

Conference

ConferenceAdvanced Concepts for Intelligent Vision Systems 2016
Abbreviated titleAcivs 2016
CountryItaly
CityLecce
Period24/10/1627/10/16
Internet address

Keywords

  • video analytics
  • multi-camera
  • decentralised
  • tracking
  • system architecture
  • synchronisation constraints
  • camera hand-off events
  • occlusion

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  • Cite this

    Di Caterina, G., Doshi, T., Soraghan, J. J., & Petropoulakis, L. (2016). A novel decentralised system architecture for multi-camera target tracking. In Advanced Concepts for Intelligent Vision Systems (ACIVS2016) (Vol. 10016, pp. 92-104). (Lecture Notes in Computer Science).. https://doi.org/10.1007/978-3-319-48680-2_9