Abstract
Many classic and contemporary face recognition algorithms work well on public data sets, but degrade sharply when they are used in variations lighting, expressions and images patches situation. New correlation filter designs have shown to be distortion invariant and the advantages of using images are due to the invariance to visible illumination variations. We propose a conceptually simple face recognition system that achieves a high degree of robustness and stability to illumination variation, image patches based in a simple non-linear correlation filter. The proposed technique is based on the premise that the face is an object composed of facial characteristics. The system can efficiently and effectively recognize faces under a variety of realistic conditions, using only frontal images under the proposed illuminations as training, and the results of detection and identification rate of is 96.3% in face identification, while in verification task reaches 94.6%.
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Feng, W. (2013). Research on Face Recognition under Images Patches and Variable Lighting. In: Li, S., et al. Advances in Multimedia Modeling. MMM 2013. Lecture Notes in Computer Science, vol 7732. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35725-1_14
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DOI: https://doi.org/10.1007/978-3-642-35725-1_14
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