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A multiresolution 3D morphable face model and fitting framework

  • 3D morphable face models are a powerful tool in computer vision. They consist of a PCA model of face shape and colour information and allow to reconstruct a 3D face from a single 2D image. 3D morphable face models are used for 3D head pose estimation, face analysis, face recognition, and, more recently, facial landmark detection and tracking. However, they are not as widely used as 2D methods - the process of building and using a 3D model is much more involved. In this paper, we present the Surrey Face Model, a multi resolution 3D morphable model that we make available to the public for non-commercial purposes. The model contains different mesh resolution levels and landmark point annotations as well as metadata for texture remapping. Accompanying the model is a lightweight open-source C++ library designed with simplicity and ease of integration as its foremost goals. In addition to basic functionality, it contains pose estimation and face frontalisation algorithms. With the tools presented in this paper, we aim to close two gaps. First, by offering different model resolution levels and fast fitting functionality, we enable the use of a 3D Morphable Model in time-critical applications like tracking. Second, the software library makes it easy for the community to adopt the 3D morphable face model in their research, and it offers a public place for collaboration.

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Author of HS ReutlingenRätsch, Matthias
Erschienen in:VISIGRAPP 2016 : proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, Rome, Italy, February 27 - 29, 2016. - Vol. 4
Place of publication:Setúbal, Portugal
Editor:Nadia Magnenat-Thalmann
Document Type:Conference proceeding
Publication year:2016
Tag:3D face reconstruction; 3D morphable face model; face model fitting; pose estimation
Page Number:8
First Page:79
Last Page:86
DDC classes:620 Ingenieurwissenschaften und Maschinenbau
Open access?:Ja
Licence (German):License Logo  Open Access