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Surveillance with automated positioning and tracking of subjects and vehicles in 3D is desired in many defence and security applications. Camera systems with stereo or multiple cameras are often used for 3D positioning. In such systems, accurate camera calibration is needed to obtain a reliable 3D position estimate. There is also a need for automated camera calibration to facilitate fast deployment of semi-mobile multi-camera 3D positioning systems. In this paper we investigate a method for automatic calibration of the extrinsic camera parameters (relative camera pose and orientation) of a multi-camera positioning system. It is based on estimation of the essential matrix between each camera pair using the 5-point method for intrinsically calibrated cameras. The method is compared to a manual calibration method using real HD video data from a field trial with a multicamera positioning system. The method is also evaluated on simulated data from a stereo camera model. The results show that the reprojection error of the automated camera calibration method is close to or smaller than the error for the manual calibration method and that the automated calibration method can replace the manual calibration.

Stand-off THz imaging to detect concealed treats is a coming technique for security applications. A THz sensor can provide high resolution 3D imagery of a scene. However, efficient scene scanning and management of the THz sensor is a challenging task due to the limited field of view of the sensor and physical scanning limitations. In this paper we discuss the requirements on a scene scanning solution and present a scene scanning technique using a multi-camera system with 3D positioning capabilities. A visual hull method is used to position subjects in the scene. The presented technique relaxes the requirements on the scanning speed of the THz sensor and facilitates an efficient scene scanning solution.