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2006 IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS'06)
Omni-Directional Camera Networks and Data Fusion for Vehicle Tracking in an Indoor Parking Lot
Sydney, NSW, Australia
November 22-November 24
ISBN: 0-7695-2688-8
ASCII Text
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Jung-Ming Wang, Ching-Ting Tsai, Shen Cherng, Sei-Wang Chen, "Omni-Directional Camera Networks and Data Fusion for Vehicle Tracking in an Indoor Parking Lot," Advanced Video and Signal Based Surveillance, IEEE Conference on, pp. 45, 2006 IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS'06), 2006.
 
 
BibTex
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@article{ 10.1109/AVSS.2006.84,
author = {Jung-Ming Wang and Ching-Ting Tsai and Shen Cherng and Sei-Wang Chen},
title = {Omni-Directional Camera Networks and Data Fusion for Vehicle Tracking in an Indoor Parking Lot},
journal ={Advanced Video and Signal Based Surveillance, IEEE Conference on},
volume = {0},
year = {2006},
isbn = {0-7695-2688-8},
pages = {45},
doi = {http://doi.ieeecomputersociety.org/10.1109/AVSS.2006.84},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Advanced Video and Signal Based Surveillance, IEEE Conference on
TI - Omni-Directional Camera Networks and Data Fusion for Vehicle Tracking in an Indoor Parking Lot
SN - 0-7695-2688-8
SP
EP
A1 - Jung-Ming Wang,
A1 - Ching-Ting Tsai,
A1 - Shen Cherng,
A1 - Sei-Wang Chen,
PY - 2006
KW - Omni-directional camera
KW - hyperbolic mirror
KW - surveillance system
KW - object tracking
KW - permutation matrix
KW - homography matrix
VL - 0
JA - Advanced Video and Signal Based Surveillance, IEEE Conference on
ER -
 
Jung-Ming Wang, National Taiwan University, Taiwan
Ching-Ting Tsai, National Taiwan Normal University, Taiwan
Shen Cherng, Cheng Shin University, Taiwan
Sei-Wang Chen, National Taiwan Normal University, Taiwan
A fixed single camera is not sufficient for monitoring a wide area. More cameras can be used, but a problem with integrating all of them will arise. In this paper, a monitoring system to detect and track moving objects in an indoor environment using multiple omni-directional cameras is proposed. Objects captured from different cameras can be integrated automatically, and we can add more cameras to enlarge the monitoring range without changing the system architecture. Such a system is currently being applied to a model of a parking lot for detecting the paths of vehicles.
Index Terms:
Omni-directional camera, hyperbolic mirror, surveillance system, object tracking, permutation matrix, homography matrix
Citation:
Jung-Ming Wang, Ching-Ting Tsai, Shen Cherng, Sei-Wang Chen, "Omni-Directional Camera Networks and Data Fusion for Vehicle Tracking in an Indoor Parking Lot," avss, pp.45, 2006 IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS'06), 2006
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