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    Measuring Visual Closeness of 3-D Models

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    FinalThesis _ Jose.pdf
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    Type
    Thesis
    Authors
    Gollaz Morales, Jose Alejandro
    Advisors
    Vigneron, Antoine E. cc
    Committee Members
    Cao, Yuanhao
    Rockwood, Alyn
    Program
    Applied Mathematics and Computational Science
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Date
    2012-09
    Permanent link to this record
    http://hdl.handle.net/10754/248714
    
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    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.
    DOI
    10.25781/KAUST-3GVS4
    ae974a485f413a2113503eed53cd6c53
    10.25781/KAUST-3GVS4
    Scopus Count
    Collections
    Applied Mathematics and Computational Science Program; Theses; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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