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In modern automated systems the usage of sensors with orthogonal measurement principles is indispensable for assuring a redundant system. The combination of laser scanners and cameras is particularly prevalent. To profit from the potential of fusing information from these sensors, the basic step is sensor registration. State of the art cross-calibration methods for laser scanners and cameras establish geometric correspondences for example by detecting checker-boards in size and form. However these approaches suffer from ambivalent features and are only usable if the laser scanner has a high scanning density. Therefore, we present a reconstruction-free and vision-based extrinsic calibration algorithm with distinct features, which was developed with special focus on low-density laser scanners and high measurement noise. Moreover, we contribute an evaluation methodology demonstrating the capability of our approach. Along with this paper, we publish the associated code.
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Gräter et al. (2016) studied this question.
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