Measuring Visual Closeness of 3-D Models

Handle URI:
http://hdl.handle.net/10754/248714
Title:
Measuring Visual Closeness of 3-D Models
Authors:
Morales, Jose A.
Abstract:
Measuring visual closeness of 3-D models is an important issue for different problems and there is still no standardized metric or algorithm to do it. The normal of a surface plays a vital role in the shading of a 3-D object. Motivated by this, we developed two applications to measure visualcloseness, introducing normal difference as a parameter in a weighted metric in Metro’s sampling approach to obtain the maximum and mean distance between 3-D models using 3-D and 6-D correspondence search structures. A visual closeness metric should provide accurate information on what the human observers would perceive as visually close objects. We performed a validation study with a group of people to evaluate the correlation of our metrics with subjective perception. The results were positive since the metrics predicted the subjective rankings more accurately than the Hausdorff distance.
Advisors:
Vigneron, Antoine
Committee Member:
Cao, Yuanhao; Rockwood, Alyn
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Program:
Applied Mathematics and Computational Science
Issue Date:
Sep-2012
Type:
Thesis
Appears in Collections:
Applied Mathematics and Computational Science Program; Theses; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.advisorVigneron, Antoineen
dc.contributor.authorMorales, Jose A.en
dc.date.accessioned2012-10-14T09:08:33Z-
dc.date.available2012-10-14T09:08:33Z-
dc.date.issued2012-09en
dc.identifier.urihttp://hdl.handle.net/10754/248714en
dc.description.abstractMeasuring visual closeness of 3-D models is an important issue for different problems and there is still no standardized metric or algorithm to do it. The normal of a surface plays a vital role in the shading of a 3-D object. Motivated by this, we developed two applications to measure visualcloseness, introducing normal difference as a parameter in a weighted metric in Metro’s sampling approach to obtain the maximum and mean distance between 3-D models using 3-D and 6-D correspondence search structures. A visual closeness metric should provide accurate information on what the human observers would perceive as visually close objects. We performed a validation study with a group of people to evaluate the correlation of our metrics with subjective perception. The results were positive since the metrics predicted the subjective rankings more accurately than the Hausdorff distance.en
dc.language.isoenen
dc.subject3-D modelsen
dc.subjectVisual closenessen
dc.subjectmeshesen
dc.subjectHausdorff distanceen
dc.titleMeasuring Visual Closeness of 3-D Modelsen
dc.typeThesisen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
thesis.degree.grantorKing Abdullah University of Science and Technologyen_GB
dc.contributor.committeememberCao, Yuanhaoen
dc.contributor.committeememberRockwood, Alynen
thesis.degree.disciplineApplied Mathematics and Computational Scienceen
thesis.degree.nameMaster of Scienceen
dc.person.id115702en
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