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Facial Information Analysis Technology for Gender and Age Estimation

2021-11-17 18:56:43
Gilheum Park, Sua Jung
arXiv_CV
             
Abstract

This is a study on facial information analysis technology for estimating gender and age, and poses are estimated using a transformation relationship matrix between the camera coordinate system and the world coordinate system for estimating the pose of a face image. Gender classification was relatively simple compared to age estimation, and age estimation was made possible using deep learning-based facial recognition technology. A comparative CNN was proposed to calculate the experimental results using the purchased database and the public database, and deep learning-based gender classification and age estimation performed at a significant level and was more robust to environmental changes compared to the existing machine learning techniques.

Abstract (translated)

URL

https://arxiv.org/abs/2111.09303

PDF

https://arxiv.org/pdf/2111.09303.pdf

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