Statistical Learning Methods for Facial Recognition

Author

Mengyi Jia, Washington University in St. LouisFollow

Date of Award

Spring 5-2017

Author's School

Graduate School of Arts and Sciences

Author's Department

Statistics

Degree Name

Master of Arts (AM/MA)

Degree Type

Thesis

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.

Language

English (en)

Chair and Committee

Todd Kuffner Department of Mathematics

Committee Members

Jimin Ding, Mladen Victor Wickerhauser

Comments

Permanent URL: https://doi.org/10.7936/K7C53J95

Recommended Citation

Jia, Mengyi, "Statistical Learning Methods for Facial Recognition" (2017). Arts & Sciences Electronic Theses and Dissertations. 1072.
https://openscholarship.wustl.edu/art_sci_etds/1072