DMCtrac: Distributed multi camera tracking

Advances in the field of computer vision enable smart cameras to cooperatively analyse scenes without human intervention. Large networks of autonomous, self-organising PTZ (pan, tilt, zoom) cameras require algorithms and protocols that make way for cooperation between multiple smart cameras (SCs). T...

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Veröffentlicht in:2008 Second ACM/IEEE International Conference on Distributed Smart Cameras S. 1 - 10
Hauptverfasser: Hoffmann, M., Wittke, M., Bernard, Y., Soleymani, R., Hahner, J.
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.09.2008
Schlagworte:
Algorithm design and analysis
Cameras
distributed tracking algorithm
PTZ tracking
Robustness
Search problems
self-organising Smart Camera network
Surveillance
Switches
track moving objects
Tracking
ISBN:1424426642, 9781424426645
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:Advances in the field of computer vision enable smart cameras to cooperatively analyse scenes without human intervention. Large networks of autonomous, self-organising PTZ (pan, tilt, zoom) cameras require algorithms and protocols that make way for cooperation between multiple smart cameras (SCs). This paper introduces a distributed algorithm for object tracking with multiple SCs (DMCtrac). The focus lies on PTZ management issues arising in large SC systems rather than on computer vision algorithms. DMCtrac enables SCs to observe objects throughout an area under surveillance by using their PTZ abilities to follow these objects. The algorithm has been evaluated by simulation of SC systems with up to 50 SCs as used for example for people tracking and traffic analysis. Results show, that DMCtrac is able to cope with large numbers of SCs and objects and is robust towards real world disturbances like communication failure.
ISBN:1424426642
9781424426645
DOI:10.1109/ICDSC.2008.4635684