Detection, classification, and collaborative tracking of multiple targets using video sensors

Authors:
P. V. Pahalawatta;D. Depalov;T. N. Pappas;A. K. Katsaggelos
Affiliations:
ECE Dept., Northwestern University, Evanston, IL;ECE Dept., Northwestern University, Evanston, IL;ECE Dept., Northwestern University, Evanston, IL;ECE Dept., Northwestern University, Evanston, IL
Venue:
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
Year:
2003

Citing 12
Cited 4

Statistical model-based change detection in moving video

Signal Processing
Model-based object tracking in monocular image sequences of road traffic scenes

International Journal of Computer Vision
Robust multiple car tracking with occlusion reasoning

ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
Self-Calibration and Metric Reconstruction Inspite of Varying and Unknown Intrinsic Camera Parameters

International Journal of Computer Vision - 1998 Marr Prize
Visual Surveillance for Moving Vehicles

International Journal of Computer Vision - Special issue on a special section on visual surveillance
A Flexible New Technique for Camera Calibration

IEEE Transactions on Pattern Analysis and Machine Intelligence
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography

Communications of the ACM
The Geometry of Multiple Images: The Laws That Govern The Formation of Images of A Scene and Some of Their Applications

The Geometry of Multiple Images: The Laws That Govern The Formation of Images of A Scene and Some of Their Applications
A Real-time Computer Vision System for Measuring Traffic Parameters

CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
In defence of the 8-point algorithm

ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Object Recognition from Local Scale-Invariant Features

ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Scale-space filtering

IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 2

Object tracking in the presence of occlusions via a camera network

Proceedings of the 6th international conference on Information processing in sensor networks
Location-Free Object Tracking on Graph Structures

EuroSSC '08 Proceedings of the 3rd European Conference on Smart Sensing and Context
Sequential use of wireless sensors for target estimation and tracking

MILCOM'03 Proceedings of the 2003 IEEE conference on Military communications - Volume I
Object tracking in the presence of occlusions using multiple cameras: A sensor network approach

ACM Transactions on Sensor Networks (TOSN)

Quantified Score

Hi-index	0.00

Visualization

Abstract

The study of collaborative, distributed, real-time sensor networks is an emerging research area. Such networks are expected to play an essential role in a number of applications such as, surveillance and tracking of vehicles in the battlefield of the future. This paper proposes an approach to detect and classify multiple targets, and collaboratively track their position and velocity utilizing video cameras. Arbitrarily placed cameras collaboratively perform self-calibration and provide complete battlefield coverage. If some of the cameras are equipped with a GPS system, they are able to metrically reconstruct the scene and determine the absolute coordinates of the tracked targets. A background subtraction scheme combined with a Markov random field based approach is used to detect the target even when it becomes stationary. Targets are continuously tracked using a distributed Kalman filter approach. As the targets move the coverage is handed over to the "best" neighboring cluster of sensors. This paper demonstrates the potential for the development of distributed optical sensor networks and addresses problems and tradeoffs associated with this particular implementation.