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A study of projections for key point based registration of panoramic terrestrial 3D laser scan 被引量:2
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作者 Hamidreza HOUSHIAR jan elseberg +1 位作者 Dorit BORRMANN Andreas NÜCHTER 《Geo-Spatial Information Science》 SCIE EI CSCD 2015年第1期11-31,共21页
This paper surveys state-of-the-art image features and descriptors for the task of 3D scan registration based on panoramic reflectance images.As modern terrestrial laser scanners digitize their environment in a spheri... This paper surveys state-of-the-art image features and descriptors for the task of 3D scan registration based on panoramic reflectance images.As modern terrestrial laser scanners digitize their environment in a spherical way,the sphere has to be projected to a two-dimensional image.To this end,we evaluate the equirectangular,the cylindrical,the Mercator,the rectilinear,the Pannini,the stereographic,and the z-axis projection.We show that the Mercator and the Pannini projection outperform the other projection methods. 展开更多
关键词 3D scan matching 3D point cloud registration automatic registration panorama images feature matching
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Skyline-Based Registration of 3D Laser Scans
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作者 Andreas Nüchter Stanislav Gutev +1 位作者 Dorit Borrmann jan elseberg 《Geo-Spatial Information Science》 2011年第2期85-90,共6页
Acquisition and registration of terrestrial 3D laser scans is a fundamental task in mapping and modeling of cities in three dimensions. To automate this task marker-flee registration methods are required. Based on the... Acquisition and registration of terrestrial 3D laser scans is a fundamental task in mapping and modeling of cities in three dimensions. To automate this task marker-flee registration methods are required. Based on the existence of skyline features, this paper proposes a novel method. The skyline features are extracted from panoramic 3D scans and encoded as strings enabling the use of string matching for merging the scans. Initial results of the proposed method in the old city center of Bremen are presented. 展开更多
关键词 LIDAR point cloud processing 3D city modeling marker-free registration place recognition
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