Abstract
In this paper, we propose a novel generative approach for face authentication, based on a Local Binary Pattern (LBP) description of the face. A generic face model is considered as a collection of LBP-histograms. Then, a client-specific model is obtained by an adaptation technique from this generic model under a probabilistic framework. We compare the proposed approach to standard state-of-the-art face authentication methods on two benchmark databases, namely XM2VTS and BANCA, associated to their experimental protocol. We also compare our approach to two state-of-the-art LBP-based face recognition techniques, that we have adapted to the verification task.
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Keywords
- Face Image
- Local Binary Pattern
- Local Binary Pattern Feature
- Local Binary Pattern Operator
- Local Binary Pattern Code
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
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Rodriguez, Y., Marcel, S. (2006). Face Authentication Using Adapted Local Binary Pattern Histograms. In: Leonardis, A., Bischof, H., Pinz, A. (eds) Computer Vision – ECCV 2006. ECCV 2006. Lecture Notes in Computer Science, vol 3954. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11744085_25
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DOI: https://doi.org/10.1007/11744085_25
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