Facial Information Analysis Technology for Gender and Age Estimation
This work addresses facial analysis for applications like security or demographics, but appears incremental as it builds on established deep learning methods.
The study tackled gender and age estimation from facial images by using deep learning-based facial recognition technology, achieving significant performance levels and greater robustness to environmental changes compared to existing machine learning techniques.
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.