Paper
1 February 1991 Invariant reconstruction of 3-D curves and surfaces
Author Affiliations +
Proceedings Volume 1382, Intelligent Robots and Computer Vision IX: Neural, Biological, and 3D Methods; (1991) https://doi.org/10.1117/12.25229
Event: Advances in Intelligent Robotics Systems, 1990, Boston, MA, United States
Abstract
The reconstruction of curves and surfaces from sparse data is an important task in many applications. In computer vision problems the reconstructed curves and surfaces generally represent some physical property of a real object in a scene. Thus the characteristics of the reconstruction process differs from straight forward fitting of smooth curves and surfaces to a set of data. Since the collected data is represented in an arbitrarily chosen coordinate system the reconstruction process should be invariant to the choice of the coordinate system (except for the transformation between the two coordinate systems). In this paper reconstruction algorithms are presented for reconstructing invariant estimates of both curves and surfaces. The reconstruction problem will be cast as an illposed inverse problem which must be stablized using a priori information about the constraint formation. Tikhonov regularization is used to form a wellposed mathematical problem statement. Examples of typical reconstructed objects are also given. 1.
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Robert L. Stevenson and Edward J. Delp III "Invariant reconstruction of 3-D curves and surfaces", Proc. SPIE 1382, Intelligent Robots and Computer Vision IX: Neural, Biological, and 3D Methods, (1 February 1991); https://doi.org/10.1117/12.25229
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Cited by 2 scholarly publications.
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KEYWORDS
Reconstruction algorithms

Computer vision technology

Machine vision

Robot vision

Robots

3D image processing

3D vision

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