IEEE: Face Recognition Based on Frontal Views Generated from Non-Frontal Images

[ashwin kumar]

This paper presents a method for face recognition across
large changes in viewpoint. Our method is based on a Morphable
Model of 3D faces that represents face-specific information
extracted from a dataset of 3D scans.
For non-frontal face recognition in 2D still images, the
Morphable Model can be incorporated in two different approaches:
In the first, it serves as a preprocessing step by
estimating the 3D shape of novel faces from the non-frontal
input images, and generating frontal views of the reconstructed
faces at a standard illumination using 3D computer
graphics. The transformed images are then fed into stateof-
the-art face recognition systems that are optimized for
frontal views. This method was shown to be extremely effective
in the Face Recognition Vendor Test FRVT 2002.
In the process of estimating the 3D shape of a face from
an image, a set of model coefficients are estimated. In the
second method, face recognition is performed directly from
these coefficients. In this paper we explain the algorithm
used to preprocess the images in FRVT 2002, present additional
FRVT 2002 results, and compare these results to
recognition from the model coefficients.

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Ashwin,
9742738409