A Multiresolution 3D Morphable Face Model and Fitting Framework. P Huber, GS Hu, R Tena, P Mortazavian, WP Koppen.

Date: February 2016.
Source: VISAPP 2016: The 11th International Conference on Computer Vision Theory and Applications, Rome, Italy.
Abstract: 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.

Article: A Multiresolution 3D Morphable Face Model and Fitting Framework.
Authors: Patrik Huber, Guosheng Hu, Rafael Tena, Pouria Mortazavian, Willem P. Koppen,
William Christmas, Matthias Rätsch and Josef Kittler. Centre for Vision, Speech & Signal Processing, University of Surrey, Guildford, United Kingdom.

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