This package contains the code that implements the following paper,
Renjie Chen and Ofir Weber. GPU-Accelerated Locally Injective Shape Deformation. ACM Transactions on Graphics, 36(6) (SIGGRAPH Asia 2017)
The app is built with a combination of MATLAB (for core computation), C++ code (for the UI) and mex/CUDA code (for GPU accelerated optimization).
The C++ source code for the OpenGL UI with MS Visual Studio C++ project files is in the glidviewer folder.
The mex/CUDA source code for the GPU accelerated optimization is in the cuHarmonic folder.
Precompiled binary for the UI and mex/CUDA are provided with the package.
- MS Windows (Windows 7/8/10)
- MATLAB (>2016b)
- A GLSL 3.3 compatible GPU.
- The OpenGL UI (glidviewer.exe)
- CUDA (Compute Capability > 3.5)
- Start MATLAB
- cd to the code folder
- Call glid_main.m within MATLAB. This will automatically open the main GUI, and load the rex shape
- For deformation, the p2p constraint can be edited by
- adding P2P constraints by left clicking on the shape
- moving the p2p target by dragging any p2p constraint
- removing constraints by right clicking the p2p
- GLID Deformer widget
- Energy, isometric energy for the optimization
- Solver, including mesh based AQP and SLIM, and harmonic subspace based Gradient Descent, LBFGS, Newton etc.
- #samples, number of samples on the boundary for the boundary integral approximation
- energy param, the paramter s for Exp Symmetric Dirichlet and AMIPS energies
- Reset Shape, reset the shape to its original state (identity mapping)
- Pause, paurse the iteration
- Clear P2P: remove all the p2p constraints.
The following libraries are needed to compile the code
- OpenGL GUI (glidviewer.exe)
- Eigen http://eigen.tuxfamily.org
- AntTweakBar http://anttweakbar.sourceforge.net
- FreeGLUT http://freeglut.sourceforge.net
- GPU-accelerated solver (cuHarmonic.mexw64)
- cub library https://nvlabs.github.io/cub/