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FGR
2008
IEEE

Statistical appearance models for automatic pose invariant face recognition

8 years 8 months ago
Statistical appearance models for automatic pose invariant face recognition
Recent pose invariant methods try to model the subject specific appearance change across pose. For this, however, almost all of the existing methods require a perfect alignment between a gallery and a probe image. In this paper we present a pose invariant face recognition method, centered on modeling joint appearance of gallery and probe images across pose, that do not require the facial landmarks to be detected as such. We propose novel extensions by introducing to use a more robust feature description as opposed to pixel-based appearances. Using such features we put forward to synthesize the non-frontal views to frontal. Furthermore, using local kernel density estimation, instead of commonly used normal density assumption, is suggested to derive the prior models. Our method does not require any strict alignment between gallery and probe images which makes it particularly attractive as compared to the existing state of the art methods. Improved recognition across a wide range of pos...
M. Saquib Sarfraz, Olaf Hellwich
Added 29 May 2010
Updated 29 May 2010
Type Conference
Year 2008
Where FGR
Authors M. Saquib Sarfraz, Olaf Hellwich
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