How Do Users Map Points Between Dissimilar Shapes?

Handle URI:
http://hdl.handle.net/10754/625254
Title:
How Do Users Map Points Between Dissimilar Shapes?
Authors:
Hecher, Michael; Guerrero, Paul; Wonka, Peter ( 0000-0003-0627-9746 ) ; Wimmer, Michael
Abstract:
Finding similar points in globally or locally similar shapes has been studied extensively through the use of various point descriptors or shape-matching methods. However, little work exists on finding similar points in dissimilar shapes. In this paper, we present the results of a study where users were given two dissimilar two-dimensional shapes and asked to map a given point in the first shape to the point in the second shape they consider most similar. We find that user mappings in this study correlate strongly with simple geometric relationships between points and shapes. To predict the probability distribution of user mappings between any pair of simple two-dimensional shapes, two distinct statistical models are defined using these relationships. We perform a thorough validation of the accuracy of these predictions and compare our models qualitatively and quantitatively to well-known shape-matching methods. Using our predictive models, we propose an approach to map objects or procedural content between different shapes in different design scenarios.
KAUST Department:
Visual Computing Center (VCC)
Citation:
Hecher M, Guerrero P, Wonka P, Wimmer M (2017) How Do Users Map Points Between Dissimilar Shapes? IEEE Transactions on Visualization and Computer Graphics: 1–1. Available: http://dx.doi.org/10.1109/TVCG.2017.2730877.
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
IEEE Transactions on Visualization and Computer Graphics
Issue Date:
25-Jul-2017
DOI:
10.1109/TVCG.2017.2730877
Type:
Article
ISSN:
1077-2626
Sponsors:
This research was partially financed by the Austrian Science Fund project Nr. FWF P24600-N23.
Additional Links:
http://ieeexplore.ieee.org/document/7990196/
Appears in Collections:
Articles; Visual Computing Center (VCC)

Full metadata record

DC FieldValue Language
dc.contributor.authorHecher, Michaelen
dc.contributor.authorGuerrero, Paulen
dc.contributor.authorWonka, Peteren
dc.contributor.authorWimmer, Michaelen
dc.date.accessioned2017-07-26T06:19:10Z-
dc.date.available2017-07-26T06:19:10Z-
dc.date.issued2017-07-25en
dc.identifier.citationHecher M, Guerrero P, Wonka P, Wimmer M (2017) How Do Users Map Points Between Dissimilar Shapes? IEEE Transactions on Visualization and Computer Graphics: 1–1. Available: http://dx.doi.org/10.1109/TVCG.2017.2730877.en
dc.identifier.issn1077-2626en
dc.identifier.doi10.1109/TVCG.2017.2730877en
dc.identifier.urihttp://hdl.handle.net/10754/625254-
dc.description.abstractFinding similar points in globally or locally similar shapes has been studied extensively through the use of various point descriptors or shape-matching methods. However, little work exists on finding similar points in dissimilar shapes. In this paper, we present the results of a study where users were given two dissimilar two-dimensional shapes and asked to map a given point in the first shape to the point in the second shape they consider most similar. We find that user mappings in this study correlate strongly with simple geometric relationships between points and shapes. To predict the probability distribution of user mappings between any pair of simple two-dimensional shapes, two distinct statistical models are defined using these relationships. We perform a thorough validation of the accuracy of these predictions and compare our models qualitatively and quantitatively to well-known shape-matching methods. Using our predictive models, we propose an approach to map objects or procedural content between different shapes in different design scenarios.en
dc.description.sponsorshipThis research was partially financed by the Austrian Science Fund project Nr. FWF P24600-N23.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.urlhttp://ieeexplore.ieee.org/document/7990196/en
dc.rights(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.en
dc.subjectComputational modelingen
dc.subjectCorrelationen
dc.subjectPredictive modelsen
dc.subjectSemanticsen
dc.subjectShapeen
dc.subjectThree-dimensional displaysen
dc.subjectTwo dimensional displaysen
dc.titleHow Do Users Map Points Between Dissimilar Shapes?en
dc.typeArticleen
dc.contributor.departmentVisual Computing Center (VCC)en
dc.identifier.journalIEEE Transactions on Visualization and Computer Graphicsen
dc.eprint.versionPost-printen
dc.contributor.institutionInstitut for Computergraphik und Algorithmen, Technische Universitat Wien, 27259 Wien, Wien Austria 1040en
dc.contributor.institutionDepartment of Computer Science, University College London, London, London United Kingdom of Great Britain and Northern Irelanden
dc.contributor.institutionInstitute of Computer Graphics and Algorithms, Vienna University of Technology, Vienna, Vienna Austria 1140en
kaust.authorWonka, Peteren
All Items in KAUST are protected by copyright, with all rights reserved, unless otherwise indicated.