Abstract
Mobile light detection and ranging (LiDAR) systems are widely used to generate precise 3-D spatial information, which in turn aids a variety of applications such as digital building model generation, transportation corridor asset management, telecommunications, precision agriculture, and infrastructure monitoring. Integrating such systems with one or more cameras would allow forward and backward projection between imagery and LiDAR data, thus facilitating several other high-level data processing activities, such as reliable feature extraction and colorization of point cloudsv. To increase the registration accuracy of point clouds derived from LiDAR data and imagery, along with their accuracy with respect to the ground truth, a simultaneous estimation of the mounting parameters relating the different laser scanners and cameras to the onboard global navigation satellite system (GNSS)/inertial navigation system (INS) unit is vital. This paper proposes a calibration procedure that directly estimates the mounting parameters for several spinning multibeam laser scanners and cameras onboard an airborne or terrestrial mobile platform. This procedure is based on the use of conjugate points and linear/planar features in overlapping images and point clouds derived from different drive-runs/flight lines. In order to increase the efficiency of semi-automatic conjugate feature extraction from the LiDAR data, specifically designed calibration boards covered by highly reflective surfaces that could be easily deployed and set up within an outdoor environment are used in this study. An experimental setup is used to evaluate the performance of the proposed calibration procedure for both airborne and terrestrial mobile mapping systems through the a posteriori variance factor of the least squares adjustment procedure and the quality of fit of the adjusted LiDAR point cloud and image points to linear/planar surfaces before and after the calibration process.
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