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231224s2015 xx |||||o 00| ||eng c |
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|a 10.1109/TIP.2015.2412379
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|a eng
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|a Punnappurath, Abhijith
|e verfasserin
|4 aut
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|a Face recognition across non-uniform motion blur, illumination, and pose
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|c 2015
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|a Text
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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|a Date Completed 14.12.2015
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|a Date Revised 01.04.2015
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a Existing methods for performing face recognition in the presence of blur are based on the convolution model and cannot handle non-uniform blurring situations that frequently arise from tilts and rotations in hand-held cameras. In this paper, we propose a methodology for face recognition in the presence of space-varying motion blur comprising of arbitrarily-shaped kernels. We model the blurred face as a convex combination of geometrically transformed instances of the focused gallery face, and show that the set of all images obtained by non-uniformly blurring a given image forms a convex set. We first propose a non-uniform blur-robust algorithm by making use of the assumption of a sparse camera trajectory in the camera motion space to build an energy function with l1 -norm constraint on the camera motion. The framework is then extended to handle illumination variations by exploiting the fact that the set of all images obtained from a face image by non-uniform blurring and changing the illumination forms a bi-convex set. Finally, we propose an elegant extension to also account for variations in pose
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|a Journal Article
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|a Research Support, U.S. Gov't, Non-P.H.S.
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| 700 |
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|a Rajagopalan, Ambasamudram Narayanan
|e verfasserin
|4 aut
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| 700 |
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|a Taheri, Sima
|e verfasserin
|4 aut
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| 700 |
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|a Chellappa, Rama
|e verfasserin
|4 aut
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| 700 |
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|a Seetharaman, Guna
|e verfasserin
|4 aut
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|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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|g 24(2015), 7 vom: 01. Juli, Seite 2067-82
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|g year:2015
|g number:7
|g day:01
|g month:07
|g pages:2067-82
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|u http://dx.doi.org/10.1109/TIP.2015.2412379
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