UID:
almahu_9948621519302882
Umfang:
XXII, 127 p.
,
online resource.
Ausgabe:
1st ed. 2004.
ISBN:
9783540286271
Serie:
Lecture Notes in Computer Science, 3151
Inhalt:
Due to the continuing progress of sensor technology, the availability of 3-D cameras is already foreseeable. These cameras are capable of generating a large set of measurement points within a very short time. There are a variety of 3-D camera applications in the fields of robotics, rapid product development and digital factories. In order to not only visualize the point cloud but also to recognize 3-D object models from the point cloud and then further process them in CAD systems, efficient and stable algorithms for 3-D information processing are required. For the automatic segmentation and recognition of such geometric primitives as plane, sphere, cylinder, cone and torus in a 3-D point cloud, efficient software has recently been developed at the Fraunhofer IPA by Sung Joon Ahn. This book describes in detail the complete set of 'best-fit' algorithms for general curves and surfaces in space which are employed in the Fraunhofer software.
Anmerkung:
1. Introduction -- 2. Least-Squares Orthogonal Distance Fitting -- 3. Orthogonal Distance Fitting of Implicit Curves and Surfaces -- 4. Orthogonal Distance Fitting of Parametric Curves and Surfaces -- 5. Object Reconstruction from Unordered Point Cloud -- 6. Conclusions.
In:
Springer Nature eBook
Weitere Ausg.:
Printed edition: ISBN 9783540239666
Weitere Ausg.:
Printed edition: ISBN 9783662209462
Sprache:
Englisch
URL:
https://doi.org/10.1007/b104017
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