Omni-Directional Camera Networks and Data Fusion for Vehicle Tracking in an Indoor Parking Lot

Authors:
Jung-Ming Wang;Ching-Ting Tsai;Shen Cherng;Sei-Wang Chen
Affiliations:
National Taiwan University, Taiwan;National Taiwan Normal University, Taiwan;Cheng Shin University, Taiwan;National Taiwan Normal University, Taiwan
Venue:
AVSS '06 Proceedings of the IEEE International Conference on Video and Signal Based Surveillance
Year:
2006

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Generation of environmental representation of a large indoor parking lot

ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part II

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Abstract

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.