Type of Document Master's Thesis Author Bellino, Kathleen Ann Author's Email Address firstname.lastname@example.org 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
- active contours
Date of Defense 2002-04-27 Availability unrestricted AbstractReal-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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