Discovering Structured Variations Via Template Matching

Duygu Ceylan; Minh Dang; Niloy J. Mitra; Boris Neubert; Mark Pauly

doi:10.1111/cgf.12788

Discovering Structured Variations Via Template Matching

Duygu Ceylan, Minh Dang, Niloy J. Mitra, Boris Neubert, Mark Pauly

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

Understanding patterns of variation from raw measurement data remains a central goal of shape analysis. Such an understanding reveals which elements are repeated, or how elements can be derived as structured variations from a common base element. We investigate this problem in the context of 3D acquisitions of buildings. Utilizing a set of template models, we discover geometric similarities across a set of building elements. Each template is equipped with a deformation model that defines variations of a base geometry. Central to our algorithm is a simultaneous template matching and deformation analysis that detects patterns across building elements by extracting similarities in the deformation modes of their matching templates. We demonstrate that such an analysis can successfully detect structured variations even for noisy and incomplete data.

Original language	English (US)
Pages (from-to)	76-88
Number of pages	13
Journal	Computer Graphics Forum
Volume	36
Issue number	1
DOIs	https://doi.org/10.1111/cgf.12788
State	Published - Jan 1 2017
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2016 The Authors Computer Graphics Forum © 2016 The Eurographics Association and John Wiley & Sons Ltd.

Keywords

I.3.5 [Computer Graphics]: Computational Geometry and Object Modelling
shape analysis
template matching

ASJC Scopus subject areas

Computer Graphics and Computer-Aided Design

Access to Document

10.1111/cgf.12788

Cite this

@article{944c7af7603743dd8b162a6984d84aaf,

title = "Discovering Structured Variations Via Template Matching",

abstract = "Understanding patterns of variation from raw measurement data remains a central goal of shape analysis. Such an understanding reveals which elements are repeated, or how elements can be derived as structured variations from a common base element. We investigate this problem in the context of 3D acquisitions of buildings. Utilizing a set of template models, we discover geometric similarities across a set of building elements. Each template is equipped with a deformation model that defines variations of a base geometry. Central to our algorithm is a simultaneous template matching and deformation analysis that detects patterns across building elements by extracting similarities in the deformation modes of their matching templates. We demonstrate that such an analysis can successfully detect structured variations even for noisy and incomplete data.",

keywords = "I.3.5 [Computer Graphics]: Computational Geometry and Object Modelling, shape analysis, template matching",

author = "Duygu Ceylan and Minh Dang and Mitra, {Niloy J.} and Boris Neubert and Mark Pauly",

note = "Publisher Copyright: {\textcopyright} 2016 The Authors Computer Graphics Forum {\textcopyright} 2016 The Eurographics Association and John Wiley & Sons Ltd.",

year = "2017",

month = jan,

day = "1",

doi = "10.1111/cgf.12788",

language = "English (US)",

volume = "36",

pages = "76--88",

journal = "Computer Graphics Forum",

issn = "0167-7055",

publisher = "Wiley-Blackwell Publishing Ltd",

number = "1",

}

TY - JOUR

T1 - Discovering Structured Variations Via Template Matching

AU - Ceylan, Duygu

AU - Dang, Minh

AU - Mitra, Niloy J.

AU - Neubert, Boris

AU - Pauly, Mark

PY - 2017/1/1

Y1 - 2017/1/1

N2 - Understanding patterns of variation from raw measurement data remains a central goal of shape analysis. Such an understanding reveals which elements are repeated, or how elements can be derived as structured variations from a common base element. We investigate this problem in the context of 3D acquisitions of buildings. Utilizing a set of template models, we discover geometric similarities across a set of building elements. Each template is equipped with a deformation model that defines variations of a base geometry. Central to our algorithm is a simultaneous template matching and deformation analysis that detects patterns across building elements by extracting similarities in the deformation modes of their matching templates. We demonstrate that such an analysis can successfully detect structured variations even for noisy and incomplete data.

AB - Understanding patterns of variation from raw measurement data remains a central goal of shape analysis. Such an understanding reveals which elements are repeated, or how elements can be derived as structured variations from a common base element. We investigate this problem in the context of 3D acquisitions of buildings. Utilizing a set of template models, we discover geometric similarities across a set of building elements. Each template is equipped with a deformation model that defines variations of a base geometry. Central to our algorithm is a simultaneous template matching and deformation analysis that detects patterns across building elements by extracting similarities in the deformation modes of their matching templates. We demonstrate that such an analysis can successfully detect structured variations even for noisy and incomplete data.

KW - I.3.5 [Computer Graphics]: Computational Geometry and Object Modelling

KW - shape analysis

KW - template matching

UR - http://www.scopus.com/inward/record.url?scp=84953335059&partnerID=8YFLogxK

U2 - 10.1111/cgf.12788

DO - 10.1111/cgf.12788

M3 - Article

AN - SCOPUS:84953335059

SN - 0167-7055

VL - 36

SP - 76

EP - 88

JO - Computer Graphics Forum

JF - Computer Graphics Forum

IS - 1

ER -

Discovering Structured Variations Via Template Matching

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this