Robust active shape model via hierarchical feature extraction with sfs-optimized convolution neural network for invariant human age classification

Syeda Amna Rizwan, Ahmad Jalal, Munkhjargal Gochoo, Kibum Kim

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

The features and appearance of the human face are affected greatly by aging. A human face is an important aspect for human age identification from childhood through adulthood. Alt-hough many traits are used in human age estimation, this article discusses age classification using salient texture and facial landmark feature vectors. We propose a novel human age classification (HAC) model that can localize landmark points of the face. A robust multi-perspective view-based Active Shape Model (ASM) is generated and age classification is achieved using Convolution Neural Network (CNN). The HAC model is subdivided into the following steps: (1) at first, a face is detected using aYCbCr color segmentation model; (2) landmark localization is done on the face using a connected components approach and a ridge contour method; (3) an Active Shape Model (ASM) is generated on the face using three-sided polygon meshes and perpendicular bisection of a triangle; (4) feature extraction is achieved using anthropometric model, carnio-facial development, interior angle formulation, wrinkle detection and heat maps; (5) Sequential Forward Selection (SFS) is used to select the most ideal set of features; and (6) finally, the Convolution Neural Network (CNN) model is used to classify according to age in the correct age group. The proposed system outperforms existing statistical state-of-the-art HAC methods in terms of classification accuracy, achieving 91.58% with The Images of Groups dataset, 92.62% with the OUI Adience dataset and 94.59% with the FG-NET dataset. The system is applicable to many research areas including access control, surveillance monitoring, human–machine interaction and self-identification.

Original languageEnglish
Article number465
Pages (from-to)1-24
Number of pages24
JournalElectronics (Switzerland)
Volume10
Issue number4
DOIs
Publication statusPublished - Feb 2 2021

Keywords

  • Active Shape Model
  • Anthropometric model
  • Deep learning method
  • Face detection
  • Landmark localization
  • Sequential Forward Selection

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Hardware and Architecture
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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