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    Modeling and Fitting 3D Shapes via Shape Grammar

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    Name:
    MS_THESIS_AHMED_ABDELREHEEM_MAY_2022.pdf
    Size:
    4.297Mb
    Format:
    PDF
    Description:
    MS Thesis
    Embargo End Date:
    2023-09-08
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    Type
    Thesis
    Authors
    Abdelreheem, Ahmed cc
    Advisors
    Wonka, Peter cc
    Committee members
    Viola, Ivan cc
    Hadwiger, Markus cc
    Program
    Computer Science
    KAUST Department
    Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
    Date
    2022-05-31
    Embargo End Date
    2023-09-08
    Permanent link to this record
    http://hdl.handle.net/10754/681019
    
    Metadata
    Show full item record
    Access Restrictions
    At the time of archiving, the student author of this thesis opted to temporarily restrict access to it. The full text of this thesis will become available to the public after the expiration of the embargo on 2023-09-08.
    Abstract
    In this thesis, we introduce a 3D Shape Grammar for generating man-made objects and an optimization algorithm to fit the structure and parameters of the grammar to a given point cloud. While simple grammars, e.g. for bounding box arrangements, have been used to define prior knowledge for reconstruction before, we take this approach to the next level, by attempting to fit complex grammars with many rules, many parameters, and curved geometric primitives. To tackle this challenge, we propose two major components. First, we propose a new shape grammar framework suitable to describe man-made objects. We also develop a complex rule set for one particular shape class, chairs, to highlight the expressiveness of the shape grammar framework. Our rule set can represent up to 55.7k unique structures. An essential design requirement of the grammar was to make it differentiable for a shape-fitting application. Second, we propose a probabilistic framework to fit the shape of grammar to a point cloud. We combine probabilistic sampling of the grammar structure with differentiable optimization of grammar parameters to that effect.
    Citation
    Abdelreheem, A. (2022). Modeling and Fitting 3D Shapes via Shape Grammar [KAUST Research Repository]. https://doi.org/10.25781/KAUST-40747
    DOI
    10.25781/KAUST-40747
    ae974a485f413a2113503eed53cd6c53
    10.25781/KAUST-40747
    Scopus Count
    Collections
    MS Theses; Computer Science Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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