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Automatic registration of large range datasets with spin-images
Authors:Alberto Guarnieri  Antonio Vettore  Martina Camarda  Costantino Domenica
Affiliation:aCIRGEO, Interdepartment Research Center for Geomatics, University of Padova, Viale dell’università 16, 35020 Legnaro, Padova, Italy;bDIASS Technical, University of Bari, Viale del Turismo 8, 74100 Taranto, Italy
Abstract:Terrestrial laser scanning technique has represented one of the more advances occurred in the last years in the field of data acquisition. Time-of-Flight (TOF) systems provide a fast and reliable tool to measure millions of 3D points allowing a very effective and dense measurement of the surface geometry. Nowadays, the generation of high quality 3D models is a practice applied to different kind of objects: small or medium size artworks, parts of human body, cars, buildings, civil infrastructures (like dams, bridges, plants, etc.) and whole archaeological sites as well. In most cases, in order to capture the whole object geometry a number of single scans need to be acquired from different positions and then stitched together (i.e. registered each other) to generate the full 3D model. The automatization of the registration of multiple scans acquired from a terrestrial laser scanner (TLS) still represents a very attractive research field. The chance to automatically align several point clouds would reduce processing costs in terms of time and human resources. In addition it would allow even non-specialist users to produce 3D models with good quality. This paper contributes to this research area by presenting a method for the automatic registration of very dense point clouds acquired by TLS systems. The proposed solution is an extension to large datasets of an automatic range data registration procedure we developed a few years ago for the modelling of point clouds acquired with close-range laser scanners. Such procedure, based on the spin-images (SIs) algorithm, has been then improved with the introduction of a multi-resolution method that generates a pyramid of spin-images in order to speed up the matching between adjacent scans. The results we present show that this method can be successfully applied for the automatic registration of high density laser scans of complex and large structures of Cultural Heritage.
Keywords:Terrestrial Laser Scanner   3D modelling   Spin-images   Automatic registration   Cultural heritage   Point clouds
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