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Automatic Deployment of Omni-Directional Cameras for Vehicle Tracking and Surveillance in an Indoor Parking Lot

By 張祥利, 林士祺, 方瓊瑤, 王俊明, 陳世旺, Shyang-Lih Chang, Shih-Ch Lin, Chiung-Yao Fang, Jung-Ming Wang and Sei-Wang Chen


[[abstract]]In this paper, we consider the problem of using as few omni-directional (OD) cameras as possible to monitor an indoor parking lot. We formulate this problem as a covering problem in which the obstacle-free area of the parking lot is to be covered by the integrated fields of view (FOV) of the OD cameras. The proposed approach consists of four steps: preprocessing, path planning, camera deployment, and generation of an environment map. In the preprocessing step, three off-line tasks are carried out: digitization of the floor plan of the parking lot, calibration of the OD cameras, and parameter estimation. In the path planning step, we transform the 2D covering problem into a 1D problem by finding a path with as few turns as possible while winding through the obstacle-free region of the parking lot. The obtained path is then used in the camera deployment step in which the path guides the locating of cameras with the goal of using as few cameras as possible for efficiently monitoring the entire parking lot. Finally, an environment map is generated from the resulting camera deployment. Such a map would be useful for a number of applications, including carport planning, multi-camera coordination, vehicle tracking, and security surveillance. A series of experiments were conducted to demonstrate the feasibility of the proposed approach.

Topics: Covering problem;Omni-directional cameras;Camera calibration;Path planning;Camera deployment;Environment map, [[classification]]42
Year: 2011
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