Abstract
Facial recognition techniques have become increasingly popular in recent decades. This thesis investigates the performance of several methods applied to two different face databases, under a variety of poses and illumination settings. PCA, LDA and KNN are compared and contrasted in terms of their accuracy and processing time.
Committee Chair
Todd Kuffner Department of Mathematics
Committee Members
Jimin Ding, Mladen Victor Wickerhauser
Degree
Master of Arts (AM/MA)
Author's Department
Statistics
Document Type
Thesis
Date of Award
Spring 5-2017
Language
English (en)
DOI
https://doi.org/10.7936/K7C53J95
Recommended Citation
Jia, Mengyi, "Statistical Learning Methods for Facial Recognition" (2017). Arts & Sciences Theses and Dissertations. 1072.
The definitive version is available at https://doi.org/10.7936/K7C53J95
Comments
Permanent URL: https://doi.org/10.7936/K7C53J95