A 3-D assisted generative model for facial texture super- resolution

Authors:
Pouria Mortazavian;Josef Kittler;William Christmas
Affiliations:
Centre for Vision, Speech and Signal Processing, University of Surrey, United Kingdom;Centre for Vision, Speech and Signal Processing, University of Surrey, United Kingdom;Centre for Vision, Speech and Signal Processing, University of Surrey, United Kingdom
Venue:
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Year:
2009

Citing 14
Cited 0

Improving image resolution using subpixel motion

Pattern Recognition Letters
Improving resolution by image registration

CVGIP: Graphical Models and Image Processing
Improved resolution from subpixel shifted pictures

CVGIP: Graphical Models and Image Processing
A non-parametric multi-scale statistical model for natural images

NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Learning Low-Level Vision

International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
Example-Based Super-Resolution

IEEE Computer Graphics and Applications
Limits on Super-Resolution and How to Break Them

IEEE Transactions on Pattern Analysis and Machine Intelligence
Reconstruction of a high-resolution image by simultaneous registration, restoration, and interpolation of low-resolution images

ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol.2)-Volume 2 - Volume 2
An Improved Two-Step Approach to Hallucinating Faces

ICIG '04 Proceedings of the Third International Conference on Image and Graphics
Ensemble of Piecewise FDA Based on Spatial Histograms of Local (Gabor) Binary Patterns for Face Recognition

ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
Hallucinating face by eigentransformation

IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Extraction of high-resolution frames from video sequences

IEEE Transactions on Image Processing
Joint MAP registration and high-resolution image estimation using a sequence of undersampled images

IEEE Transactions on Image Processing
Generalized Face Super-Resolution

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper describes an example-based Bayesian method for 3D-assisted pose-independent facial texture super-resolution. The method utilizes a 3D morphable model to map facial texture from a 2D face image to a pose- and shape-normalized texture map and vice versa. The center piece of this method is a generative model to describe the process of forming an image from a pose- and shape-normalized texture map. The goal is to reconstruct a high-resolution texture map given an low-resolution face image. The prior knowledge about the sought high-resolution texture is incorporated into the Bayesian framework by using a recognition-based prior that encourages the gradient values of the texture map to be close to some predicted values. We develop the generative model and formulate the problem as MAP estimation. The results show that this framework is capable of performing pose-independent face recognition even when the sample set only contains exemplar face images with frontal pose. We present results in frontal and nonfrontal poses. We also demonstrate that the technique can be utilized to improve face recognition results when the probe images have a lower resolution compared to the gallery images.