Title :
Omni-Directional Camera Networks and Data Fusion for Vehicle Tracking in an Indoor Parking Lot
Author :
Wang, Jung-Ming ; Tsai, Ching-Ting ; Cherng, Shen ; Chen, Sei-Wang
Author_Institution :
National Taiwan University, Taiwan
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.
Keywords :
Automotive engineering; Cameras; Computer science; Computerized monitoring; Data engineering; Data mining; Indoor environments; Object detection; Surveillance; Vehicles; Omni-directional camera; homography matrix; hyperbolic mirror; object tracking; permutation matrix; surveillance system;
Conference_Titel :
Video and Signal Based Surveillance, 2006. AVSS '06. IEEE International Conference on
Conference_Location :
Sydney, Australia
Print_ISBN :
0-7695-2688-8
DOI :
10.1109/AVSS.2006.84
