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This paper compares the outcomes of Principal Component Analysis (PCA) on head and face shape within a military population using two distinct input data types: one-dimensional (1D) linear measurements and three-dimensional (3D) coordinates. This study offers an informative perspective on the potential variations in PCA results, elucidating the advantages and disadvantages of each input method to the broader discourse on selecting appropriate methods for robust analytical outcomes.

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Comparative Analysis of Head and Face Shape Using Principal Component Analysis with 1D and 3D Data

  • 会议论文

  • 发表日期：

    2025年

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  • Hyegjoo E. Choi-Rokas,
  • K. Han Kim,
  • Peng Li,
  • K. Blake Mitchell

摘要

This paper compares the outcomes of Principal Component Analysis (PCA) on head and face shape within a military population using two distinct input data types: one-dimensional (1D) linear measurements and three-dimensional (3D) coordinates. This study offers an informative perspective on the potential variations in PCA results, elucidating the advantages and disadvantages of each input method to the broader discourse on selecting appropriate methods for robust analytical outcomes.