Calibration of an outdoor distributed camera network with a 3D point cloud

Journal Article (2014)









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Outdoor camera networks are becoming ubiquitous in critical urban areas of largest cities around the world. Although current applications of camera networks are mostly tailored to video surveillance, recent research projects are exploiting their use to aid robotic systems in people assisting tasks. Such systems require precise calibration of the internal and external parameters of the distributed camera network. Despite the fact that camera calibration has been an extensively studied topic, the development of practical methods for user-assisted calibration that minimize user intervention time and maximize precision still pose significant challenges. These camera systems have non-overlapping fields of view and are subject to environmental stress, and are likely to suffer frequent recalibration. In this paper we propose the use of a 3D map covering the area to support the calibration process, and develop an automated method that allows quick and precise calibration of a large camera network. We present two cases of study of the proposed calibration method, one is the calibration of the Barcelona Robt Lab camera network, which also includes direct mappings (homographies) between image coordinates and world points in the ground plane (walking areas) to support person and robot detection and localization algorithms. The second case consist on improving the GPS positioning of geo-tagged images taken with a mobile device in the FME patio at UPC.



Scientific reference

A.A. Ortega, M. Silva, E.H. Teniente, R. Ferreira, A.J. Bernardino Malheiro, J. Gaspar and J. Andrade-Cetto. Calibration of an outdoor distributed camera network with a 3D point cloud. Sensors, 14(8): 13708-13729, 2014.