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Open Access Automatic Point Cloud Registration Using a Single Octagonal Lamp Pole

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Registration is an essential procedure for merging point clouds defined in different coordinate systems associated to different scanner positions and orientations. It is usually the first step before the point clouds are further processed to provide spatial information of a scene to support engineering applications. In this paper, a new automatic registration method based on a novel geometric model of a polygonal object is presented. Since the cross section of the shaft of many lamp poles is octagonal, registration based on an octagonal pyramid model is proposed. The presented method only requires a single, common octagonal lamp pole observed in both point clouds, though actual overlap of the point clouds is not strictly required. It can be performed as long as the model parameters can be estimated by fitting the point observations to the model. Moreover, no user interaction is needed to derive approximate values, so the proposed registration can be completely automated. Three independent datasets captured by two scanners were used to verify the method. The registration accuracies in the horizontal and vertical directions were up to 11.7 mm and 4.4 mm at approximately 62 m and 17 m away from the scanner, respectively. With such high accuracies, the estimated registration parameters can serve as a set of initial parameters for fine registration using algorithm such as the iterative closest point (ICP).

Document Type: Research Article

Publication date: 01 April 2016

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  • The official journal of the American Society for Photogrammetry and Remote Sensing - the Imaging and Geospatial Information Society (ASPRS). This highly respected publication covers all facets of photogrammetry and remote sensing methods and technologies.

    Founded in 1934, the American Society for Photogrammetry and Remote Sensing (ASPRS) is a scientific association serving over 7,000 professional members around the world. Our mission is to advance knowledge and improve understanding of mapping sciences to promote the responsible applications of photogrammetry, remote sensing, geographic information systems (GIS), and supporting technologies.
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