Morphable Face Models - An Open Framework

Thomas Gerig, Andreas Morel-Forster, Clemens Blumer, Bernhard Egger, Marcel Lüthi +2 more
9/25/2017
cs.CV

Official code: unibas-gravis/basel-face-pipeline (233 stars, Apache-2.0, last commit 2023-10-25).

Abstract

In this paper, we present a novel open-source pipeline for face registration based on Gaussian processes as well as an application to face image analysis. Non-rigid registration of faces is significant for many applications in computer vision, such as the construction of 3D Morphable face models (3DMMs). Gaussian Process Morphable Models (GPMMs) unify a variety of non-rigid deformation models with B-splines and PCA models as examples. GPMM separate problem specific requirements from the registration algorithm by incorporating domain-specific adaptions as a prior model. The novelties of this paper are the following: (i) We present a strategy and modeling technique for face registration that considers symmetry, multi-scale and spatially-varying details. The registration is applied to neutral faces and facial expressions. (ii) We release an open-source software framework for registration and model-building, demonstrated on the publicly available BU3D-FE database. The released pipeline also contains an implementation of an Analysis-by-Synthesis model adaption of 2D face images, tested on the Multi-PIE and LFW database. This enables the community to reproduce, evaluate and compare the individual steps of registration to model-building and 3D/2D model fitting. (iii) Along with the framework release, we publish a new version of the Basel Face Model (BFM-2017) with an improved age distribution and an additional facial expression model.

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Code Implementations(1)

Apache-2.0
23334ScalaSep 25, 20172 years agoApache-2.0

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Cite this paper

@article{gerig2017morphable,
  title  = {Morphable Face Models - An Open Framework},
  author = {Thomas Gerig and Andreas Morel-Forster and Clemens Blumer and Bernhard Egger and Marcel Lüthi and Sandro Schönborn and Thomas Vetter},
  year   = {2017},
  eprint = {1709.08398},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/1709.08398}
}

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