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Volumetric shape description of range data using “Blobby Model”

Author:

Shigeru MurakiAuthors Info & Claims

ACM SIGGRAPH Computer Graphics, Volume 25, Issue 4

Pages 227 - 235

https://doi.org/10.1145/127719.122743

Published: 01 July 1991 Publication History

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Abstract

Recently in the field of computer vision, there have been many attempts to obtain a symbolic shape description of an object by fitting simple primitives to the range data of the object. In this paper, we introduce the "Blobby Model" for automatically generating a shape description from range data. This model can express a 3D surface as an isosurface of a scalar field which is produced by a number of field generating primitives. The fields from many primitives are blended with each other and can form a very complicated shape. To determine the number and distribution of primitives required to adequately represent a complex 3D surface, an energy function is minimized which measures the shape difference between the range data and the "Blobby Model". We start with a single primitive and introduce more primitives by splitting each primitive into two further primitives so as to reduce the energy value. In this manner, the shape of the 3D object is slowly recovered as the isosurface produced by many primitives. We have successfully applied this method to human face range data and typical results are shown. The method herein does not require any prior range segmentation.

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Volumetric shape description of range data using “Blobby Model”
1. Computing methodologies

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Published In

cover image ACM SIGGRAPH Computer Graphics

ACM SIGGRAPH Computer Graphics Volume 25, Issue 4

July 1991

340 pages

ISSN:0097-8930

DOI:10.1145/127719

Editor:
Richard J. Beach
Xerox PARC, Palo Alto, CA

Issue’s Table of Contents

SIGGRAPH '91: Proceedings of the 18th annual conference on Computer graphics and interactive techniques
July 1991
393 pages
ISBN:0897914368
DOI:10.1145/122718
Chairman:
James J. Thomas
Battelle Pacific Northwest Labs., Richland, WA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 July 1991

Published in SIGGRAPH Volume 25, Issue 4

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Wang HYuan LXiong JMao J(2022)The relaxed implicit randomized algebraic reconstruction technique for curve and surface reconstructionComputers and Graphics10.1016/j.cag.2021.11.004102:C(9-17)Online publication date: 1-Feb-2022
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