Comparative study of human age estimation based on hand-crafted and deep face features
Date
2016-10-03Author
Belver Mielgo, Carlos
Metadata
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In the past few years, human facial age estimation has drawn a lot of attention
in the computer vision and pattern recognition communities because of its important
applications in age-based image retrieval, security control and surveillance, biomet-
rics, human-computer interaction (HCI) and social robotics. In connection with these
investigations, estimating the age of a person from the numerical analysis of his/her
face image is a relatively new topic. Also, in problems such as Image Classification
the Deep Neural Networks have given the best results in some areas including age
estimation.
In this work we use three hand-crafted features as well as five deep features
that can be obtained from pre-trained deep convolutional neural networks. We do a
comparative study of the obtained age estimation results with these features.