Least Squares Orthogonal Distance Fitting of Curves and Surfaces in Space [electronic resource] / by Sung Joon Ahn.

By: Ahn, Sung Joon [author.]Contributor(s): SpringerLink (Online service)Material type: TextTextLanguage: English Series: Lecture Notes in Computer Science: 3151Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2004Description: XXII, 127 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783540286271Subject(s): Computer science | Computer software | Electronic data processing | Computer graphics | Computer vision | Discrete groups | Engineering mathematics | Computer Science | Numeric Computing | Algorithm Analysis and Problem Complexity | Computer Graphics | Image Processing and Computer Vision | Appl.Mathematics/Computational Methods of Engineering | Convex and Discrete GeometryAdditional physical formats: Printed edition:: No titleDDC classification: 518 LOC classification: QA297-299.4Online resources: Click here to access online
Contents:
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 eBooksSummary: Due to the continuing progress of sensor technology, the availability of 3-D c- eras is already foreseeable. These cameras are capable of generating a large set of measurement points within a very short time. There is a variety of 3-D camera - plications in the ?elds of robotics, rapid product development and digital factories. In order to not only visualize the point cloud but also to recognize 3-D object m- els from the point cloud and then further process them in CAD systems, ef?cient and stable algorithms for 3-D information processing are required. For the au- matic segmentation and recognition of such geometric primitives as plane, sphere, cylinder, cone and torus in a 3-D point cloud, ef?cient software has recently been developed at the Fraunhofer IPA by Sung Joon Ahn. This book describes in detail the complete set of ‘best-?t’ algorithms for general curves and surfaces in space which are employed in the Fraunhofer software.
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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.

Due to the continuing progress of sensor technology, the availability of 3-D c- eras is already foreseeable. These cameras are capable of generating a large set of measurement points within a very short time. There is a variety of 3-D camera - plications in the ?elds of robotics, rapid product development and digital factories. In order to not only visualize the point cloud but also to recognize 3-D object m- els from the point cloud and then further process them in CAD systems, ef?cient and stable algorithms for 3-D information processing are required. For the au- matic segmentation and recognition of such geometric primitives as plane, sphere, cylinder, cone and torus in a 3-D point cloud, ef?cient software has recently been developed at the Fraunhofer IPA by Sung Joon Ahn. This book describes in detail the complete set of ‘best-?t’ algorithms for general curves and surfaces in space which are employed in the Fraunhofer software.

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