Face Recognition based on Frontal Views generated from Non-Frontal Images
Volker Blanz, Patrick Grother, Jonathon Phillipps and Thomas Vetter
In: CVPR'05, 20-25 June, San Diego USA.
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-speci c 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 rst, 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 coef cients are estimated. In the second method, face recognition is performed directly from these coef cients. 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.
|EPrint Type:||Conference or Workshop Item (Paper)|
|Project Keyword:||Project Keyword UNSPECIFIED|
|Deposited By:||Thomas Vetter|
|Deposited On:||29 November 2005|