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
  • real-time face recognition
  • alignment
  • rotation
  • active contours
Date of Defense 2002-04-27
Availability unrestricted
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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