Sparse-Data Based 3D Surface Reconstruction for Cartoon and Map

Bin Wu*, Talal Rahman, Xue-Cheng TAI

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

A model combining the first-order and the second-order variational regularizations for the purpose of 3D surface reconstruction based on 2D sparse data is proposed. The model includes a hybrid fidelity constraint which allows the initial conditions to be switched flexibly between vectors and elevations. A numerical algorithm based on the augmented Lagrangian method is also proposed. The numerical experiments are presented, showing its excellent performance both in designing cartoon characters, as well as in recovering oriented three dimensional maps from contours or points with elevation information.

Original languageEnglish
Pages (from-to)47-64
Number of pages18
JournalMathematics and Visualization
Volume0
Issue number221219
DOIs
Publication statusPublished - 2018
EventInternational conference on Imaging, Vision and Learning Based on Optimization and PDEs, IVLOPDE 2016 - Bergen, Norway
Duration: 29 Aug 20162 Sep 2016

Scopus Subject Areas

  • Modelling and Simulation
  • Geometry and Topology
  • Computer Graphics and Computer-Aided Design
  • Applied Mathematics

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