University of Surrey

Test tubes in the lab Research in the ATI Dance Research

Gaussian Mixture 3D Morphable Face Model

Koppen, Paul, Feng, Zhenhua, Kittler, Josef, Awais, Muhammad, Christmas, William, Wu, Xiao-Jun and Yin, He-Feng (2017) Gaussian Mixture 3D Morphable Face Model Pattern Recognition, 74. pp. 617-628.

2017_GM3DMM.pdf - Accepted version Manuscript

Download (4MB) | Preview


3D Morphable Face Models (3DMM) have been used in pattern recognition for some time now. They have been applied as a basis for 3D face recognition, as well as in an assistive role for 2D face recognition to perform geometric and photometric normalisation of the input image, or in 2D face recognition system training. The statistical distribution underlying 3DMM is Gaussian. However, the single-Gaussian model seems at odds with reality when we consider different cohorts of data, e.g. Black and Chinese faces. Their means are clearly different. This paper introduces the Gaussian Mixture 3DMM (GM-3DMM) which models the global population as a mixture of Gaussian subpopulations, each with its own mean. The proposed GM-3DMM extends the traditional 3DMM naturally, by adopting a shared covariance structure to mitigate small sample estimation problems associated with data in high dimensional spaces. We construct a GM-3DMM, the training of which involves a multiple cohort dataset, SURREY-JNU, comprising 942 3D face scans of people with mixed backgrounds. Experiments in fitting the GM-3DMM to 2D face images to facilitate their geometric and photometric normalisation for pose and illumination invariant face recognition demonstrate the merits of the proposed mixture of Gaussians 3D face model.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
Kittler, Josef
Awais, Muhammad
Wu, Xiao-Jun
Yin, He-Feng
Date : 9 September 2017
Funders : EPSRC
DOI : 10.1016/j.patcog.2017.09.006
Copyright Disclaimer : © 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license. (
Uncontrolled Keywords : Gaussian-mixture Model; 3D Morphable Model; 3D Face Reconstruction; Face Model Fitting; Face Recognition
Depositing User : Jane Hindle
Date Deposited : 11 Sep 2017 13:41
Last Modified : 11 Dec 2018 11:23

Actions (login required)

View Item View Item


Downloads per month over past year

Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800