Sparse-data Based 3D Surface Reconstruction for Cartoon and MapMS49

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 numer ical expriments are presented, showing its excellent performance both in designing cartoon characters, as well as in recovering oriented mountain surfaces. This talk is based on joint works with Bin Wu and Talal Rahman.

This presentation is part of Minisymposium “MS49 - Image Restoration, Enhancement and Related Algorithms (4 parts)
organized by: Weihong Guo (Case Western Reserve University) , Ke Chen (University of Liverpool) , Xue-Cheng Tai (Hong Kong Baptist University) , Guohui Song (Clarkson University) .

Xue-Cheng Tai (Hong Kong Baptist University)
computer graphics, computer vision, partial differential equation models