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Robust method in photogrammetric reconstruction of geometric primitives in solid modeling

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TitleInfo
Title
Robust method in photogrammetric reconstruction of geometric primitives in solid modeling
Name (type = personal)
NamePart (type = family)
Yang
NamePart (type = given)
Xiang
NamePart (type = date)
1987-
DisplayForm
Xiang Yang
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Gea
NamePart (type = given)
Hae Chang
DisplayForm
Hae Chang Gea
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
chair
Name (type = personal)
NamePart (type = family)
Meer
NamePart (type = given)
Peter
DisplayForm
Peter Meer
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
co-chair
Name (type = personal)
NamePart (type = family)
Bai
NamePart (type = given)
Xiaoli
DisplayForm
Xiaoli Bai
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Lee
NamePart (type = given)
Howon
DisplayForm
Howon Lee
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Kulikowski
NamePart (type = given)
Casimir
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Casimir Kulikowski
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
outside member
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
School of Graduate Studies
Role
RoleTerm (authority = RULIB)
school
TypeOfResource
Text
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theses
OriginInfo
DateCreated (qualifier = exact)
2017
DateOther (qualifier = exact); (type = degree)
2017-10
CopyrightDate (encoding = w3cdtf); (qualifier = exact)
2017
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
The 3D point cloud is a widely used data format obtained from scanning a 3D model, either by using active 3D laser range scanners or passive photogrammetric methods. Since the topological information in a point cloud is captured on 3D point level, the inverse design cannot be carried out directly on the data. The point cloud is first segmented into various geometric primitives, such as planes, spheres and cylinders, then the modification and redesign of solid model can be more easily achieved. A robust estimator is required to detect the multiple inlier structures while filtering out the outliers. In this dissertation, we present a new robust algorithm which processes each structure independently. The user gives only the number of elemental subsets for random sampling, which is also required in other robust algorithms. This method provides a general solution of robust estimation, and no tuning of other parameters are required for particular estimation tasks. The scales of the structures (tolerance of error) are estimated adaptively and no threshold is involved in spite of different objective functions. After classifying all the input data, the segmented structures are sorted by their strengths and the strongest inlier structures come out at the top. Like any robust estimators, this algorithm also has limitations which are described in detail. To illustrate its efficiency and robustness, the algorithm is tested on various synthetic and real examples in both 2D and 3D. We extend its applications through the entire process of the structure from motion method, to reconstruct the 3D point cloud from a sequence of 2D images. We automatically estimate and fit the 3D surfaces from the 3D point samples, without generating surface normals or mesh model. The designer can interact with the 3D points conveniently and direct modification of point cloud becomes applicable.
Subject (authority = RUETD)
Topic
Mechanical and Aerospace Engineering
Subject (authority = ETD-LCSH)
Topic
Robust statistics
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_8214
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (xiii, 100 p. : ill.)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Note (type = statement of responsibility)
by Xiang Yang
RelatedItem (type = host)
TitleInfo
Title
School of Graduate Studies Electronic Theses and Dissertations
Identifier (type = local)
rucore10001600001
Location
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NjNbRU
Identifier (type = doi)
doi:10.7282/T3WM1HKK
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Yang
GivenName
Xiang
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2017-05-18 12:36:30
AssociatedEntity
Name
XIANG YANG
Role
Copyright holder
Affiliation
Rutgers University. School of Graduate Studies
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical

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2017-05-18T10:57:27
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