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...

Full description

Bibliographic Details
Main Authors: Schlessman Jason, Chen Cheng-Yao, Singh JaswinderP, Wolf WayneH, Velipasalar Senem
Format: Article
Language:English
Published: SpringerOpen 2008-01-01
Series:EURASIP Journal on Image and Video Processing
Online Access:http://jivp.eurasipjournals.com/content/2008/542808
id doaj-aa60c6f132b84a099faccb8f5e4fc84a
record_format Article
spelling 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
work_keys_str_mv AT schlessmanjason ascalableclusteredcamerasystemformultipleobjecttracking
AT chenchengyao ascalableclusteredcamerasystemformultipleobjecttracking
AT singhjaswinderp ascalableclusteredcamerasystemformultipleobjecttracking
AT wolfwayneh ascalableclusteredcamerasystemformultipleobjecttracking
AT velipasalarsenem ascalableclusteredcamerasystemformultipleobjecttracking
AT schlessmanjason scalableclusteredcamerasystemformultipleobjecttracking
AT chenchengyao scalableclusteredcamerasystemformultipleobjecttracking
AT singhjaswinderp scalableclusteredcamerasystemformultipleobjecttracking
AT wolfwayneh scalableclusteredcamerasystemformultipleobjecttracking
AT velipasalarsenem scalableclusteredcamerasystemformultipleobjecttracking
_version_ 1725818750211457024