A tool for 3D face models aligment. With a GUI.

Shape Registrator works with 3D model and supports .mat (Matlab), .wrl (WRML) and .off (Open File Format) file formats.

• Displacement map can now be saved as a Pickle file.
• Target model can be rotated, in order to provide a good starting point for CPD algorithm.
• Source model is now shown in the target section while registrated.

1. Clone repo.
2. pip install -r requirements.txt
3. Run main.py

1. Load two models, you can choose between .mat, .wrl + .bnd and .off formats.
2. Select the amount of points to be used and the CPD version: rigid, affine or deformable.
3. "Registrate", and wait for the result.

In the log box you can see the registration error and some messages.

.mat files have to contain a '3ddata' field storing 3D points coordinates (a Nx3 matrix) and a 'landmarks3d' witch stores the landmarks coordinates (Nx3 matrix).

.wrl files should be paired with a .bnd file storing the landmarks coordinates. If a .png image with the same name is aviable, it will be used for the background of the plot tool.

.off files must contain 3D points coordinates, faces are not mandatory and will be ignored.

In the very heart of the application there's the Coherent Point Drift algorithm[1], witch allows to registrate two point sets regardless from the transformation's nature. In fact, CPD provides three kind of transformation: rigid, affine and deformable; with crescent grades of freedom.

It's possible to control the quantity of the points involved in the registration process: you can choose to keep all of them (100%) or to reduce until 30% of original number. The sampling policy used is uniform and casual.

Reduce the amount of points makes the registration process faster, but - only for affine and deformable case - the transformation matrices can't be used to process the entire point set. However, we can take advantage of this option in the rigid case.

A requirements.txt is provided, in order to be used with pip

The application was tested so far with Python 3.7 x64 operating on Windows 10 and Ubuntu 16.04 LTS. Should work on MacOs as well, since PyQt5 is cross-platform.

[1] Andriy Myronenko and Xubo Song, "Point Set Registration: Coherent Point Drift", IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 32, issue 12, pp. 2262-2275, 15 May 2009 {link}

[2] Alessandro Soci and Gabriele Barlacchi, AlessandroSoci/3DMM-Facial-Expression-from-Webcam

[3] Alessandro Sestini and Francesco Lombardi, fralomba/Facial-Expression-Prediction