Stammdaten

CamSim: A Distributed Smart Camera Network Simulator
Untertitel:
Kurzfassung: Smart cameras allow pre-processing of video data on the camera instead of sending it to a remote server for further analysis. Having a network of smart cameras allows various vision tasks to be processed in a distributed fashion. While cameras may have different tasks, we concentrate on distributed tracking in smart camera networks. This application introduces various highly interesting problems. Firstly, how can conflicting goals be satisfied such as cameras in the network try to track objects while also trying to keep communication overhead low? Secondly, how can cameras in the network selfadapt in response to the behaviour of objects and changes in scenarios, to ensure continued efficient performance? Thirdly, how can cameras organise themselves to improve the overall network’s performance and efficiency? This paper presents a simulation environment, called CamSim, allowing distributed self-adaptation and self-organisation algorithms to be tested, without setting up a physical smart camera network. The simulation tool is written in Java and hence allows high portability between different operating systems. Relaxing various problems of computer vision and network communication enables a focus on implementing and testing new self-adaptation and self-organisation algorithms for cameras to use.
Schlagworte:
Publikationstyp: Beitrag in Sammelwerk (Autorenschaft)
Art der Veröffentlichung Printversion
Erschienen in: Proceedings of the 7th IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops, SASOW
Proceedings of the 7th IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops, SASOW
zur Publikation
 ( IEEE; A. Diaconescu )
Erscheinungdatum: 11.09.2013
Titel der Serie: -
Bandnummer: -
Erstveröffentlichung: Ja
Seite: S. 2 - 2

Identifikatoren

ISBN: -
ISSN: -
DOI: -
AC-Nummer: -
Homepage:
Open Access
  • Kein Open-Access

Zuordnung

Organisation Adresse
Fakultät für Technische Wissenschaften
 
Institut für Vernetzte und Eingebettete Systeme
Universitätsstraße 65-67
9020  Klagenfurt am Wörthersee
Österreich
  -993640
   kornelia.lienbacher@aau.at
https://nes.aau.at/
zur Organisation
Universitätsstraße 65-67
AT - 9020  Klagenfurt am Wörthersee

Kategorisierung

Sachgebiete
  • 1108 - Informatik
  • 2502 - Allgemeine Elektrotechnik
Forschungscluster
  • Selbstorganisierende Systeme
Peer Reviewed
  • Ja
Publikationsfokus
  • Science to Science (Qualitätsindikator: II)
Klassifikationsraster der zugeordneten Organisationseinheiten:
Arbeitsgruppen Keine Arbeitsgruppe ausgewählt

Kooperationen

Keine Kooperationspartner ausgewählt

Beiträge der Publikation

Keine verknüpften Publikationen vorhanden