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2005
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Creating Invariance to "Nuisance Parameters" in Face Recognition

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Creating Invariance to "Nuisance Parameters" in Face Recognition
A major goal for face recognition is to identify faces where the pose of the probe is different from the stored face. Typical feature vectors vary more with pose than with identity, leading to very poor recognition performance. We propose a non-linear many-to-one mapping from a conventional feature space to a new space constructed so that each individual has a unique feature vector regardless of pose. Training data is used to implicitly parameterize the position of the multi-dimensional face manifold by pose. We introduce a co-ordinate transform which depends on the position on the manifold. This transform is chosen so that different poses of the same face are mapped to the same feature vector. The same approach is applied to illumination changes. We investigate different methods for creating features which are invariant to both pose and illumination. We provide a metric to assess the discriminability of the resulting features. Our technique increases the discriminability of faces und...
Simon J. D. Prince, James H. Elder
Added 12 Oct 2009
Updated 29 Oct 2009
Type Conference
Year 2005
Where CVPR
Authors Simon J. D. Prince, James H. Elder
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