Automatically assigned DDC number: 006696

Manually assigned DDC number: 006693

Number of references: 8

Title: Adaptive Reconstruction of Surfaces and Scalar Fields from Dense Scattered Trivariate Data

Author:

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Subject: Chandrajit L. Bajaj,Fausto Bernardini,Guoliang Xu Adaptive Reconstruction of Surfaces and Scalar Fields from Dense Scattered Trivariate Data

Description: In this paper, we propose an approach to model a set of trivariate dense and scattered data on an unknownmanifold by the zero contour of the C 1 piecewise tri-quadratic or tri-cubic polynomial. The C 1 function approximates the data over an octree-like mesh in an adaptive fashion. At the same time, and applying the same techniques, a scalar field (scalar values associated with the sampled surface points) is also modeled as a C 1 piecewise polynomial function defined on the reconstructed surface. The reconstructed surface and field can be used to visualize and interact with the data in a variety of ways. 1 Introduction In many important cases, a physical phenomenon is measured by sampling the value of a scalar or vector field at points on the surface of some object. For example, one might have sampled the temperature on the surface of a jet-engine, or the acceleration of a fluid flow on the wing of an airplane. Other cases of interest are electroencephalogram data on the surface ...

Contributor: The Pennsylvania State University CiteSeer Archives

Publisher: unknown

Date: 1995-04-02

Pubyear: 1995

Format: ps

Identifier: http://citeseer.ist.psu.edu/150215.html

Source: ftp://ftp.cs.purdue.edu/pub/shastra/pubs/viz95surfrec-bw.ps.gz

Language: en

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Rights: unrestricted

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