Abstract. With the smartphone boom, positioning oneself on the Earth's surface has become something common. Everyone know how to uses their smartphone to get their location or finding their way. However, achieve centimetric accuracy on positioning still a topical issue that arouses considerable interest. Geodetic GNSS antennas are currently used for this field, but their price is incompatible with the mass market applications (autonomous cars, drones, machine automation, photogrammetry, etc.). In this paper, an approach to improve the Android smartphone positioning is presented using low-cost GNSS receiver. Requested by Syslor, a start-up working in buried networks, the society want to enhance its customer services. The purpose of this study is to present a method to reach centimetric localisation of smartphones for augmented reality and as-built 3D plans applications.
<p><strong>Abstract.</strong> Laser scanning and photogrammetry methods have seen immense development in the last years. From bulky inaccessible systems, these two 3D recording systems has become more or less ubiquitous, which is also the case in the heritage domain. However, automation in point cloud classification and semantic annotation remains a much studied topic. In this paper, an approach to help the classification of point cloud is presented using the help of existing 2D drawings. The 2D drawings are registered unto the 3D data, to then be used as a support in the 3D modeling step. The developed approach includes the computation of the point cloud cross section and detection of feature points. This is then used in a 3D transformation followed by ICP refinement to properly register the vectorized 2D drawing on the 3D point cloud. Results show that the developed algorithm manages to register the 2D drawing automatically and with promising results. The automatically registered 2D drawing, which often times already includes semantic information, was then used to help classify the point cloud into several architectural classes.</p>
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