Affine-Invariant Fourier Descriptions for Feature-Based Facial Recognition
Date of Award
2006
Document Type
Thesis
Degree Name
Bachelors
Department
Natural Sciences
First Advisor
Mullins, David
Keywords
Fourier, Affine, Facial Recognition
Area of Concentration
Computer Science
Abstract
Facial recognition systems have been commercially employed in efforts to halt identity theft, eliminate duplicate voters, catch criminals, and automate the collection of demographic data. Despite the high demand for this technology, no existing software has provided a reliable means of identifying individuals in a scene using a stored database of images. In this paper, I explore one aspect of face recognition, known as image classification. This deals with the way in which images are parameterized and stored prior to performing comparisons. First, I explore the obstacles present in classifying facial images. Next, I examine the various approaches to resolving these issues. In researching the state of the art of facial recognition, I hypothesized that a geometric based feature-oriented method would be the most effective technique. I chose to implement this by using Fourier descriptors modified for affine invariance, as this would yield a substantial amount of information while excluding noisy and irrelevant data. I coded a program called OpenFace which utilizes affine-invariant Fourier descriptors. After performing a number of tests, OpenFace showed favorable results. I believe that this is a promising technology for facial classification.
Recommended Citation
Schechter, Erica, "Affine-Invariant Fourier Descriptions for Feature-Based Facial Recognition" (2006). Theses & ETDs. 3707.
https://digitalcommons.ncf.edu/theses_etds/3707
Rights
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The New College of Florida, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.