Aesthetics of Curve Approximation Public Deposited

http://ir.library.oregonstate.edu/concern/undergraduate_thesis_or_projects/5138jg95v

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  • In this work we propose a curve approximation method that operates in the curvature domain. The curvature is represented using one of several different types of basis functions (linear, quadratic, spline, sinusoidal, orthogonal polynomial), and the curve's geometry is reconstructed from that curvature basis. Our hypothesis is that different curvature bases will result in different aesthetics for the reconstructed curve. We conducted a user study comparing multiple curvature bases, both for aesthetics and similarity to the original curve, and found statistically significant differences in how people ranked the reconstructed curve's aesthetics and similarity. To support adaptive curve fitting we developed a fitting algorithm that matches the original curve's geometry and explicitly accounts for corners. We also extend this algorithm to 3D.
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  • description.provenance : Made available in DSpace on 2016-05-17T14:42:00Z (GMT). No. of bitstreams: 2 license_rdf: 1536 bytes, checksum: df76b173e7954a20718100d078b240a8 (MD5) LippincottKeithD2016.pdf: 18240895 bytes, checksum: deea9a9f928e2021c6b297a425c7820c (MD5)
  • description.provenance : Approved for entry into archive by Patricia Black(patricia.black@oregonstate.edu) on 2016-05-17T14:41:59Z (GMT) No. of bitstreams: 2 license_rdf: 1536 bytes, checksum: df76b173e7954a20718100d078b240a8 (MD5) LippincottKeithD2016.pdf: 18240895 bytes, checksum: deea9a9f928e2021c6b297a425c7820c (MD5)
  • description.provenance : Submitted by Keith Lippincott (lippinke@oregonstate.edu) on 2016-05-16T22:55:48Z No. of bitstreams: 2 license_rdf: 1536 bytes, checksum: df76b173e7954a20718100d078b240a8 (MD5) LippincottKeithD2016.pdf: 18240895 bytes, checksum: deea9a9f928e2021c6b297a425c7820c (MD5)

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Last modified: 07/27/2017

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