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Representation and depiction of 2D shapes using parts
Descriptive
TypeOfResource
Text
TitleInfo
(ID = T-1)
Title
Representation and depiction of 2D shapes using parts
Identifier
ETD_2750
Identifier
(type = hdl)
http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000056580
Language
LanguageTerm
(authority = ISO639-2);
(type = code)
eng
Genre
(authority = marcgt)
theses
Subject
(ID = SBJ-1);
(authority = RUETD)
Topic
Computer Science
Subject
(ID = SBJ-2);
(authority = ETD-LCSH)
Topic
Computer graphics
Subject
(ID = SBJ-3);
(authority = ETD-LCSH)
Topic
Rendering (Computer graphics)
Subject
(ID = SBJ-4);
(authority = ETD-LCSH)
Topic
Computer vision
Abstract
(type = abstract)
We describe a 2D shape abstraction system that aims to clarify the structure without loss of the expressiveness of the original shape. To do this, traditional approaches in computer graphics typically use simplification techniques based on local adjustments of vertices, edges and faces. However, this thesis argues that an effective depiction can benefit from a computational representation compatible with a human’s understanding of the shape. To support this argument, we first present a system that parses a 2D planar shape into a part-based structure that approximately respects the structural organization in human perception. Then we show that simplifications of this representation align with the common artistic practices in shape abstraction, in which only prominent parts are preserved and the visual structures are more clarified than using traditional simplification methods based on local adaptation of geometric details. To compute the part structure of a given shape, we first propose that a part connects to the rest of the shape via its transition. Then we use a simple but general model to mathematically locate and describe this transition. We show that our model generalizes previously discovered theories on how the human visual system parses a shape into parts. It also provides a plausible way of explanatory shape analysis that requires clean pruning of parts without leaving attachment traces. Following insights from cognitive science, we have designed a set of heuristics to resolve ambiguities in the representation of the shape. A set of stroke-based tools is designed so that the user can interact with the system to guide the shape analysis as well as to evaluate and optimize the performance of the parser. Geometric thresholds and part selection tools are provided for the user to specify a subset of the part structure computed from the above step. The abstraction is done by simply reconstructing the shape from this subset. The reconstruction respects the geometric properties of the original part attachment and allows topological alternations of the structure resulting from elimination of less salient parts, which greatly improves the flexibility in the reconstruction. The perceptual study we have conducted confirms that human subjects indeed prefer our abstractions over the traditional 2D shape simplifications by Douglas-Peucker or Progressive Meshes, both of which try to approximate certain geometric properties during the simplifications.
PhysicalDescription
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electronic resource
Extent
ix, 151 p. : ill., maps
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application/pdf
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text/xml
Note
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Ph.D.
Note
(type = bibliography)
Includes bibliographical references
Note
(type = vita)
Includes vita
Note
(type = statement of responsibility)
by Xiaofeng Mi
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Mi
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Xiaofeng
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1978-
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author
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Xiaofeng Mi
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DeCarlo
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Doug
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chair
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Advisory Committee
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Doug DeCarlo
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Nealen
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Andrew
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internal member
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Advisory Committee
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Andrew Nealen
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Stone
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Matthew
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Advisory Committee
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Matthew Stone
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Finkelstein
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Adam
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Adam Finkelstein
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Singh
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Manish
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outside member
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Advisory Committee
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Manish Singh
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Rutgers University
Role
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degree grantor
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Graduate School - New Brunswick
Role
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school
OriginInfo
DateCreated
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2010
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2010-10
Place
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xx
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TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier
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ETD
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TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
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rucore19991600001
Location
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NjNbRU
Identifier
(type = doi)
doi:10.7282/T30G3JWB
Genre
(authority = ExL-Esploro)
ETD doctoral
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Rights
RightsDeclaration
(AUTHORITY = GS);
(ID = rulibRdec0006)
The author owns the copyright to this work.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
RightsHolder
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Name
FamilyName
Mi
GivenName
Xiaofeng
Role
Copyright Holder
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Type
Permission or license
DateTime
2010-06-09 00:00:03
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Name
Xiaofeng Mi
Affiliation
Rutgers University. Graduate School - New Brunswick
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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.
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Technical
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ETD
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application/pdf
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application/x-tar
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11100160
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Statistical Profile