NDLI: Efficient adaptive simplification of massive meshes

Content Provider	IEEE Xplore Digital Library
Author	Shaffer, E. Garland, M.
Copyright Year	2001
Description	Author affiliation: Dept. of Comput. Sci., Illinois Univ., Urbana, IL, USA (Shaffer, E.; Garland, M.)
Abstract	The growing availability of massive polygonal models, and the inability of most existing visualization tools to work with such data, has created a pressing need for memory-efficient methods capable of simplifying very large meshes. In this paper, we present a method for performing adaptive simplification of polygonal meshes that are too large to fit in-core. Our algorithm performs two passes over an input mesh. In the first pass, the model is quantized using a uniform grid, and surface information is accumulated in the form of quadrics and dual quadrics. This sampling is then used to construct a BSP-tree in which the partitioning planes are determined by the dual quadrics. In the final pass, the original vertices are clustered using the BSP-tree, yielding an adaptive approximation of the original mesh. The BSP-tree describes a natural simplification hierarchy, making it possible to generate a progressive transmission and construct level-of-detail representations. In this way, the algorithm provides some of the features associated with more expensive edge contraction methods while maintaining greater computational efficiency. In addition to performing adaptive simplification, our algorithm exhibits output-sensitive memory requirements and allows fine control over the size of the simplified mesh.
Sponsorship	IEEE Comput. Soc. Tech. Committee on Visualization & Graphics ACM SIGGRAPH
Starting Page	127
Ending Page	551
File Size	1025867
Page Count	425
File Format	PDF
ISBN	0780372018
DOI	10.1109/VISUAL.2001.964503
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-10-21
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Clustering algorithms Data visualization Partitioning algorithms Availability Sampling methods Computational efficiency Solid modeling Data structures Pressing Programmable control
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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