PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Regression Based Non-frontal Face Synthesis for Improved Identity Verification
Yongkang Wong, Conrad Sanderson and Brian C. Lovell
In: Computer Analysis of Images and Patterns (CAIP), 2009, Muenster, Germany.


We propose a low-complexity face synthesis technique which transforms a 2D frontal view image into views at specific poses, without recourse to computationally expensive 3D analysis or iterative fitting techniques that may fail to converge. The method first divides a given image into multiple overlapping blocks, followed by synthesising a non-frontal representation through applying a multivariate linear regression model on a low-dimensional representation of each block. To demonstrate one application of the proposed technique, we augment a frontal face verification system by incorporating multi-view reference (gallery) images synthesised from the frontal view. Experiments on the pose subset of the FERET database show considerable reductions in error rates, especially for large deviations from the frontal view.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:5472
Deposited By:Conrad Sanderson
Deposited On:04 October 2009