Shape from recognition: a novel approach for 3-D face shaperecovery
Nandy, D.; Ben-Arie, J.
Image Processing, IEEE Transactions on
Volume 10, Issue 2, Feb 2001 Page(s):206 - 217
Digital Object Identifier 10.1109/83.902286
Summary:In this paper, we develop a novel framework for robust recovery of
three-dimensional (3-D) surfaces of faces from single images. The
underlying principle is shape from recognition, i.e., the idea that
pre-recognizing face parts can constrain the space of possible solutions
to the image irradiance equation, thus allowing robust recovery of the
3-D structure of a specific part. Parts of faces like nose, lips and
eyes are recognized and localized using robust expansion matching filter
templates under varying pose and illumination. Specialized
backpropagation based neural networks are then employed to recover the
3-D shape of particular face parts. Representation using principal
components allows to efficiently encode classes of objects such as nose,
lips, etc. The specialized networks are designed and trained to map the
principal component coefficients of the part images to another set of
principal component coefficients that represent the corresponding 3-D
surface shapes. To achieve robustness to viewing conditions, the network
is trained with a wide range of illumination and viewing directions. A
method for merging recovered 3-D surface regions by minimizing the sum
squared error in overlapping areas is also derived. Quantitative
analysis of the reconstruction of the surface parts in varying
illumination and pose show relatively small errors, indicating that the
method is robust and accurate. Several examples showing recovery of the
complete face also illustrate the efficacy of the approach
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