eos is a tiny 3D Morphable Face Model fitting library that provides just the bare minimum to load a model and perform camera and shape fitting. It's written in modern C++11/14.

At the moment, it mainly provides the following functionality:

• MorphableModel class to represent a 3DMM (using OpenCVs cv::Mat)
• Camera pose estimation, implementation of:
  • the Gold Standard Algorithm for estimating an affine camera matrix, from Multiple View Geometry, Hartley & Zisserman
  • a non-linear algorithm that directly estimates the pose angles and camera translation
• Shape fitting, implementation of the linear shape-to-landmarks fitting of O. Aldrian & W. Smith, Inverse Rendering of Faces with a 3D Morphable Model, PAMI 2013
• Isomap texture extraction to obtain a pose-invariant representation of the face texture.

• Tested with the following compilers: >=gcc-4.8.4, >=clang-3.5, Visual Studio 2015
• Needed dependencies for the library: Boost system (>=1.50.0), OpenCV core (>=2.4.3)

To use the library in your own project, just add the following directories to your include path:

• eos/include
• eos/3rdparty/cereal-1.1.1/include
• eos/3rdparty/glm-0.9.7.0

• Needed dependencies for the example app: CMake (>=2.8.10), Boost system, filesystem, program_options (>=1.50.0), OpenCV core, imgproc, highgui (>=2.4.3).

To build:

• copy initial_cache.cmake.template to initial_cache.cmake, edit the necessary paths
• create a build directory next to the eos folder: mkdir build; cd build
• cmake -C ../eos/initial_cache.cmake -G "<your favourite generator>" ../eos -DCMAKE_INSTALL_PREFIX=../install/
• build using your favourite tools, e.g. make; make install or open the solution in Visual Studio.

See examples/fit-model.cpp.

After make install or running the INSTALL target, an example image with landmarks can be found in install/bin/data/. The model and the necessary landmarks mapping file are installed to install/share/.

You can run the example just by running:

fit-model

Or, by manually specifying the face model, landmark vertex mappings, an image and its 2D landmarks:

fit-model -m ../share/sfm_shape_3448.bin -p ../share/ibug2did.txt -i data/image_0010.png -l data/image_0010.pts

The output is an obj file with the shape and a png with the extracted isomap. The estimated pose angles and shape coefficients are available in the code via the API.

Doxygen: http://patrikhuber.github.io/eos/doc/

The fit-model example and the Namespace List in doxygen are a good place to start.

This code is licensed under the Apache License, Version 2.0

Contributions are very welcome! (best in the form of pull requests.) Please use Github issues for any bug reports, ideas, and discussions.

If you use this code in your own work, please cite the following paper: Fitting 3D Morphable Models using Local Features, P. Huber, Z. Feng, W. Christmas, J. Kittler, M. Rätsch, IEEE International Conference on Image Processing (ICIP) 2015, Québec City, Canada (http://arxiv.org/abs/1503.02330).

go ahead!