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Resolution-Aware 3D Morphable Model

Hu, G, Chan, Chi Ho, Kittler, Josef and Christmas, B (2012) Resolution-Aware 3D Morphable Model

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The 3D Morphable Model (3DMM) is currently receiving considerable attention for human face analysis. Most existing work focuses on fitting a 3DMM to high resolution images. However, in many applications, fitting a 3DMM to low-resolution images is also important. In this paper, we propose a Resolution-Aware 3DMM (RA- 3DMM), which consists of 3 different resolution 3DMMs: High-Resolution 3DMM (HR- 3DMM), Medium-Resolution 3DMM (MR-3DMM) and Low-Resolution 3DMM (LR-3DMM). RA-3DMM can automatically select the best model to fit the input images of different resolutions. The multi-resolution model was evaluated in experiments conducted on PIE and XM2VTS databases. The experimental results verified that HR- 3DMM achieves the best performance for input image of high resolution, and MR- 3DMM and LR-3DMM worked best for medium and low resolution input images, respectively. A model selection strategy incorporated in the RA-3DMM is proposed based on these results. The RA-3DMM model has been applied to pose correction of face images ranging from high to low resolution. The face verification results obtained with the pose-corrected images show considerable performance improvement over the result without pose correction in all resolutions

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
Hu, G
Chan, Chi
Christmas, B
Date : 2012
Funders : EPSRC
DOI : 10.5244/C.26.109
Copyright Disclaimer : Copyright 2012. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms.
Depositing User : Symplectic Elements
Date Deposited : 16 Oct 2014 11:25
Last Modified : 11 Dec 2018 11:22

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