isprsarchives XXXIX B3 29 2012
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The scale-stability of DEMs derived from ASTER satellite imagery appears to offer a solution for the registration of DEMs extracted from archival aerial imagery,
The point cloud registration is then carried out by estimating the rigid transformation between two sparse point clouds where the weights of the 3D/3D correspondences are derived
The proposed method comprises following steps: (1) recognize primitives from LiDAR point cloud and roughly measure primitives’ parameters as initial values, and (2) select
The proposed method estimates the transformation parameters between reference surface and registration surface using a mathematical adjustment model.. 3D surface matching is an
For this propose we use Conditional Random Fields (CRF) for the classification of the point cloud into the classes water, mudflat, and mussel bed based on geometric and
Common knowledge used in classification is that roofs are above the ground and connect with it via vertical walls; and if a wall is not presented in
The resulting surface models have the same resolution as the input images, but global methods typically have a high processing time, which prevent their use for real world
Before starting the process of iterative pose estimation using the projected contour template, it is necessary to find the three- dimensional coordinates of points whose
