New Hybrid PCA-Based Facial Age Estimation Using Inter-Age Group Variation-Based Hierarchical Classifier

 By datasciencecentral - 2021-03-18

Description

This article was written by Tapan Kumar Sahoo & Haider Banka.  Abstract In this paper, we propose hybrid principal component analysis (HPCA) to extra…

Summary

  • In this paper, we propose hybrid principal component analysis (HPCA) to extract appearance feature of a face and inter-age group variation-based classifier (IAGVC) with regression to estimate age of a person.
  • Under HPCA, we introduce two novel methods, extended SpPCA and extended SubXPCA.
  • The issues, such as summarization of variance, variable component selection, computational complexity and classification accuracy of HPCA, have been addressed as well.
  • The experimental results on FG-NET aging database show that the proposed HPCA-based IAGVC has better classification accuracy as compared to existing classical PCA, local SpPCA and SubXPCA over all age groups.

 

Topics

  1. Machine_Learning (0.13)
  2. NLP (0.1)
  3. Backend (0.06)

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