LIDAR systems have been regarded as novel technologies for efficiently acquiring 3-D geo-spatial information, resulting in broad applications in engineering and management fields. Registration of LIDAR point clouds of consecutive scans or different platforms is a prerequisite for fully exploiting advantages of afore-mentioned applications. In this study, the authors integrate point, line and plane features, commonly seen geometric primitives and readily detected or derived from point clouds, for establishing a multi-feature 3-D similarity transformation model, both functional and stochastic, and illustrate the feasibility of the proposed methodologies on the effectiveness of employed features through theoretical identifications and experimental demonstrations.
|Number of pages||6|
|Journal||International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives|
|State||Published - 2010|
|Event||ISPRS Technical Commission III Symposium on Photogrammetric Computer Vision and Image Analysis, PCV 2010 - Saint-Mande, France|
Duration: 1 Sep 2010 → 3 Sep 2010
- 3-D similarity transformation model