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2018 | OriginalPaper | Buchkapitel

Face Recognition Across Aging Using GLBP Features

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Abstract

Face recognition over aging is still a difficult but interesting problem in pattern recognition nowadays. It has many real world applications. It is highly affected with many uncontrolled parameters like variations in head pose, expressions and illumination. Aging also varies person to person, thus makes the task more difficult. This paper includes an approach proposed by us for solving this problem. Here, we introduced a novel feature descriptor that is a combination of Gabor and LBP features called as GLBP. We used Principal Component analysis (PCA) for dimensionality reduction and k-NN as a classifier. Proposed approach is experimentally tested on popular aging datasets FGNET and MORPH. It is observed from the experimental results that our approach is better in Rank-1 recognition accuracy as a performance measure.

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Metadaten
Titel
Face Recognition Across Aging Using GLBP Features
verfasst von
Mrudula Nimbarte
K. K. Bhoyar
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-63645-0_30