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3D scan conversion of CSG models into distance volumes

Breen, David E. and Mauch, Sean and Whitaker, Ross T. (1998) 3D scan conversion of CSG models into distance volumes. In: IEEE Symposium on Volume Visualization, 1998. IEEE , Piscataway, NJ, pp. 7-14. ISBN 0-8186-9180-8. https://resolver.caltech.edu/CaltechAUTHORS:20160810-162521236

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Abstract

A distance volume is a volume dataset where the value stored at each voxel is the shortest distance to the surface of the object being represented by the volume. Distance volumes are a useful representation in a number of computer graphics applications. In this paper we present a technique for generating a distance volume with sub-voxel accuracy from one type of geometric model, a Constructive Solid Geometry (CSG) model consisting of superellipsoid primitives. The distance volume is generated in a two step process. The first step calculates the shortest distance to the CSG model at a set of points within a narrow band around the evaluated surface. Additionally, a second set of points, labeled the zero set, which lies on the CSG model’s surface are computed. A point in the zero set is associated with each point in the narrow band. Once the narrow band and zero set are calculated, a Fast Marching Method is employed to propagate the shortest distance and closest point information out to the remaining voxels in the volume. Our technique has been used to scan convert a number of CSG models, producing distance volumes which have been utilized in a variety of computer graphics applications, e.g. CSG surface evaluation, offset surface generation, and 3-D model morphing.


Item Type:Book Section
Related URLs:
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http://dx.doi.org/10.1109/SVV.1998.729579DOIPaper
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=729579PublisherPaper
Additional Information:© 1998 IEEE. We would like to thank Dr. Alan Barr and the other members of the Caltech Computer Graphics Group for their support and assistance. Timothy Doyle created the model used in Figure 9. This work was financially supported by the National Science Foundation (ASC-89-20219), as part of the STC for Computer Graphics and Scientific Visualization; the National Institute on Drug Abuse, the National Institute of Mental Health and the NSF, as part of the Human Brain Project; the Office of the Director of Defense Research and Engineering, and the Air Force Office of Scientific Research (F49620-96-1-0471), as part of the MURI program; and the Volume Visualization Program of the Office of Naval Research (N00014-97-0227). Additional equipment grants were provided by Silicon Graphics, Hewlett-Packard, IBM, and Digital Equipment Corporation. This work was initially funded by the former shareholders of the European Computer-Industry Research Centre: Bull SA, ICL PLC, and Siemens AG.
Funders:
Funding AgencyGrant Number
NSFASC-89-20219
National Institute on Drug AbuseUNSPECIFIED
National Institute of Mental Health (NIMH)UNSPECIFIED
Air Force Office of Scientific Research (AFOSR)F49620-96-1-0471
Office of Naval Research (ONR)N00014-97-0227
Silicon GraphicsUNSPECIFIED
Hewlett-PackardUNSPECIFIED
IBMUNSPECIFIED
Digital Equipment CorporationUNSPECIFIED
Bull SAUNSPECIFIED
ICL PLCUNSPECIFIED
Siemens AGUNSPECIFIED
DOI:10.1109/SVV.1998.729579
Record Number:CaltechAUTHORS:20160810-162521236
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20160810-162521236
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:69554
Collection:CaltechAUTHORS
Deposited By:INVALID USER
Deposited On:11 Aug 2016 17:30
Last Modified:11 Nov 2021 04:16

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