A fast narrow band method and its application in topology-adaptive 3-D modeling

Shuntaro Yui, Kenji Hara, Hongbin Zha, Tsutomu Hasegawa

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

We present a new fast method of modeling 3-D objects of arbitrary topology. The Level Set Methods have been used by many researchers to recover 3-D shapes of arbitrary topology. However, those methods are computationally inefficient. To reduce the computational cost, a new method named FNB (Fast Narrow Band Method) is proposed. FNB is based on the Narrow Band Method (NB) which is the well-known fast method of the Level Set Method. The main idea is to exploit the combinative use of the narrow band and the approximate distance from the front. The method has been applied in several experiments using range data and we find that our method is over 50 times faster than NB.

Original languageEnglish
Pages (from-to)122-125
Number of pages4
Journal16th IAPR International Conference on Pattern Recognition
Volume16
Issue number4
Publication statusPublished - Dec 1 2002
Externally publishedYes

Fingerprint

Topology
Costs
Experiments

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

Cite this

A fast narrow band method and its application in topology-adaptive 3-D modeling. / Yui, Shuntaro; Hara, Kenji; Zha, Hongbin; Hasegawa, Tsutomu.

In: 16th IAPR International Conference on Pattern Recognition, Vol. 16, No. 4, 01.12.2002, p. 122-125.

Research output: Contribution to journalArticle

@article{795826e952724638bec2846374de5d4a,
title = "A fast narrow band method and its application in topology-adaptive 3-D modeling",
abstract = "We present a new fast method of modeling 3-D objects of arbitrary topology. The Level Set Methods have been used by many researchers to recover 3-D shapes of arbitrary topology. However, those methods are computationally inefficient. To reduce the computational cost, a new method named FNB (Fast Narrow Band Method) is proposed. FNB is based on the Narrow Band Method (NB) which is the well-known fast method of the Level Set Method. The main idea is to exploit the combinative use of the narrow band and the approximate distance from the front. The method has been applied in several experiments using range data and we find that our method is over 50 times faster than NB.",
author = "Shuntaro Yui and Kenji Hara and Hongbin Zha and Tsutomu Hasegawa",
year = "2002",
month = "12",
day = "1",
language = "English",
volume = "16",
pages = "122--125",
journal = "16th IAPR International Conference on Pattern Recognition",
number = "4",

}

TY - JOUR

T1 - A fast narrow band method and its application in topology-adaptive 3-D modeling

AU - Yui, Shuntaro

AU - Hara, Kenji

AU - Zha, Hongbin

AU - Hasegawa, Tsutomu

PY - 2002/12/1

Y1 - 2002/12/1

N2 - We present a new fast method of modeling 3-D objects of arbitrary topology. The Level Set Methods have been used by many researchers to recover 3-D shapes of arbitrary topology. However, those methods are computationally inefficient. To reduce the computational cost, a new method named FNB (Fast Narrow Band Method) is proposed. FNB is based on the Narrow Band Method (NB) which is the well-known fast method of the Level Set Method. The main idea is to exploit the combinative use of the narrow band and the approximate distance from the front. The method has been applied in several experiments using range data and we find that our method is over 50 times faster than NB.

AB - We present a new fast method of modeling 3-D objects of arbitrary topology. The Level Set Methods have been used by many researchers to recover 3-D shapes of arbitrary topology. However, those methods are computationally inefficient. To reduce the computational cost, a new method named FNB (Fast Narrow Band Method) is proposed. FNB is based on the Narrow Band Method (NB) which is the well-known fast method of the Level Set Method. The main idea is to exploit the combinative use of the narrow band and the approximate distance from the front. The method has been applied in several experiments using range data and we find that our method is over 50 times faster than NB.

UR - http://www.scopus.com/inward/record.url?scp=33646590397&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33646590397&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:33646590397

VL - 16

SP - 122

EP - 125

JO - 16th IAPR International Conference on Pattern Recognition

JF - 16th IAPR International Conference on Pattern Recognition

IS - 4

ER -