Field-Aware Parameterization for 3D Painting

  • Songgang Xu
  • Hang Li
  • John KeyserEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11542)


We present a two-phase method that generates a near-isometric parameterization using a local chart of the surface while still being aware of the geodesic metric. During the first phase, we utilize a novel method that approximates polar coordinates to obtain a preliminary parameterization as well as the gradient of the geodesic field. For the second phase, we present a new optimization that generates a near isometric parameterization while considering the gradient field, allowing us to generate high quality parameterizations while keeping the geodesic information. This local parameterization is applied in a view-dependent 3D painting system, providing a local adaptive map computed at interactive rates.


Parameterization Painting system Geodesic 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Intel CorporationFolsomUSA
  2. 2.Texas A&M UniversityCollege StationUSA

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