Title page for ETD etd-05162002-162739

Type of Document

Master's Thesis

Author

Bellino, Kathleen Ann

Author's Email Address

kbellino@vt.edu

URN

etd-05162002-162739

Title

Computational Algorithms for Face Alignment and Recognition

Degree

Master of Science

Department

Mathematics

Advisory Committee

Advisor Name	Title
Herdman, Terry L.	Committee Chair
Borggaard, Jeffrey T.	Committee Member
Burns, John A.	Committee Member
Cliff, Eugene M.	Committee Member
King, Belinda B.	Committee Member
Wisniewski, Helena S.	Committee Member

Keywords

real-time face recognition
alignment
rotation
active contours

Date of Defense

2002-04-27

Availability

unrestricted

Abstract

Real-time face recognition has recently become available for the government and industry
due to developments in face recognition algorithms, human head detection algorithms, and faster/low cost
computers. Despite these advances, however, there are still some critical issues that affect the
performance of real-time face recognition software. This paper addresses the problem of off-centered
and out-of-pose faces in pictures, particularly in regard to the eigenface method for face recognition.
We first demonstrate how the representation of faces by the eigenface method, and ultimately the performance
of the software depend on the location of the eyes in the pictures. The eigenface method for face
recognition is described: specifically, the creation of a face basis using the singular value decomposition,
the reduction of dimension, and the unique representation of faces in the basis. Two different approaches
for aligning the eyes in images are presented. The first considers the rotation of images using
the orthogonal Procrustes Problem. The second approach looks at locating features in images using
energy-minimizing active contours. We then conclude with a simple and fast algorithm for locating faces in
images. Future research is also discussed.

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