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Journal of Zhejiang University SCIENCE A 2006 Vol.7 No.7 P.1201~1209

10.1631/jzus.2006.A1201


A general framework for progressive point-sampled geometry


Author(s):  LIU Yong-jin, TANG Kai, JONEJA Ajay

Affiliation(s):  Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China; more

Corresponding email(s):   liuyongjin@tsinghua.edu.cn, mektang@ust.hk, joneja@ust.hk

Key Words:  Progressive model, Point-sample geometry, Geometric distance, Error measure, Shape representation


LIU Yong-jin, TANG Kai, JONEJA Ajay. A general framework for progressive point-sampled geometry[J]. Journal of Zhejiang University Science A, 2006, 7(7): 1201~1209.

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author="LIU Yong-jin, TANG Kai, JONEJA Ajay",
journal="Journal of Zhejiang University Science A",
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publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2006.A1201"
}

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%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2006.A1201

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T1 - A general framework for progressive point-sampled geometry
A1 - LIU Yong-jin
A1 - TANG Kai
A1 - JONEJA Ajay
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SP - 1201
EP - 1209
%@ 1673-565X
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.2006.A1201


Abstract: 
Recently unstructured dense point sets have become a new representation of geometric shapes. In this paper we introduce a novel framework within which several usable error metrics are analyzed and the most basic properties of the progressive point-sampled geometry are characterized. Another distinct feature of the proposed framework is its compatibility with most previously proposed surface inference engines. Given the proposed framework, the performances of four representative well-reputed engines are studied and compared.

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