A Scalable Clustered Camera System for Multiple Object Tracking
<p>Abstract</p> <p>Reliable and efficient tracking of objects by multiple cameras is an important and challenging problem, which finds wide-ranging application areas. Most existing systems assume that data from multiple cameras is processed on a single processing unit or by a centr...
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Online Access: | http://jivp.eurasipjournals.com/content/2008/542808 |
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doaj-aa60c6f132b84a099faccb8f5e4fc84a2020-11-24T22:07:54ZengSpringerOpenEURASIP Journal on Image and Video Processing1687-51761687-52812008-01-0120081542808A Scalable Clustered Camera System for Multiple Object TrackingSchlessman JasonChen Cheng-YaoSingh JaswinderPWolf WayneHVelipasalar Senem<p>Abstract</p> <p>Reliable and efficient tracking of objects by multiple cameras is an important and challenging problem, which finds wide-ranging application areas. Most existing systems assume that data from multiple cameras is processed on a single processing unit or by a centralized server. However, these approaches are neither scalable nor fault tolerant. We propose multicamera algorithms that operate on <it>peer-to-peer</it> computing systems. Peer-to-peer vision systems require codesign of image processing and distributed computing algorithms as well as sophisticated communication protocols, which should be carefully designed and verified to avoid deadlocks and other problems. This paper introduces the scalable clustered camera system, which is a <it>peer-to-peer</it> multicamera system for multiple object tracking. Instead of transferring control of tracking jobs from one camera to another, each camera in the presented system performs its own tracking, keeping its own trajectories for each target object, which provides fault tolerance. A fast and robust tracking algorithm is proposed to perform tracking on each camera view, while maintaining consistent labeling. In addition, a novel communication protocol is introduced, which can handle the problems caused by communication delays and different processor loads and speeds, and incorporates variable synchronization capabilities, so as to allow flexibility with accuracy tradeoffs. This protocol was exhaustively verified by using the <it>SPIN</it> verification tool. The success of the proposed system is demonstrated on different scenarios captured by multiple cameras placed in different setups. Also, simulation and verification results for the protocol are presented.</p>http://jivp.eurasipjournals.com/content/2008/542808 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Schlessman Jason Chen Cheng-Yao Singh JaswinderP Wolf WayneH Velipasalar Senem |
spellingShingle |
Schlessman Jason Chen Cheng-Yao Singh JaswinderP Wolf WayneH Velipasalar Senem A Scalable Clustered Camera System for Multiple Object Tracking EURASIP Journal on Image and Video Processing |
author_facet |
Schlessman Jason Chen Cheng-Yao Singh JaswinderP Wolf WayneH Velipasalar Senem |
author_sort |
Schlessman Jason |
title |
A Scalable Clustered Camera System for Multiple Object Tracking |
title_short |
A Scalable Clustered Camera System for Multiple Object Tracking |
title_full |
A Scalable Clustered Camera System for Multiple Object Tracking |
title_fullStr |
A Scalable Clustered Camera System for Multiple Object Tracking |
title_full_unstemmed |
A Scalable Clustered Camera System for Multiple Object Tracking |
title_sort |
scalable clustered camera system for multiple object tracking |
publisher |
SpringerOpen |
series |
EURASIP Journal on Image and Video Processing |
issn |
1687-5176 1687-5281 |
publishDate |
2008-01-01 |
description |
<p>Abstract</p> <p>Reliable and efficient tracking of objects by multiple cameras is an important and challenging problem, which finds wide-ranging application areas. Most existing systems assume that data from multiple cameras is processed on a single processing unit or by a centralized server. However, these approaches are neither scalable nor fault tolerant. We propose multicamera algorithms that operate on <it>peer-to-peer</it> computing systems. Peer-to-peer vision systems require codesign of image processing and distributed computing algorithms as well as sophisticated communication protocols, which should be carefully designed and verified to avoid deadlocks and other problems. This paper introduces the scalable clustered camera system, which is a <it>peer-to-peer</it> multicamera system for multiple object tracking. Instead of transferring control of tracking jobs from one camera to another, each camera in the presented system performs its own tracking, keeping its own trajectories for each target object, which provides fault tolerance. A fast and robust tracking algorithm is proposed to perform tracking on each camera view, while maintaining consistent labeling. In addition, a novel communication protocol is introduced, which can handle the problems caused by communication delays and different processor loads and speeds, and incorporates variable synchronization capabilities, so as to allow flexibility with accuracy tradeoffs. This protocol was exhaustively verified by using the <it>SPIN</it> verification tool. The success of the proposed system is demonstrated on different scenarios captured by multiple cameras placed in different setups. Also, simulation and verification results for the protocol are presented.</p> |
url |
http://jivp.eurasipjournals.com/content/2008/542808 |
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