Andrew Mullen

Abstract

Face recognition is a rapidly advancing research topic due to the large number of applications that can benefit from it. Face recognition consists of determining whether a known face is present in an image and is typically composed of four distinct steps. These steps are face detection, face alignment, feature extraction, and face classification [1]. The leading application for face recognition is video surveillance. The majority of current research in face recognition has focused on determining if a face is present in an image, and if so, which subject in a known database is the closest match. This Thesis deals with face matching, which is a subset of face recognition, focusing on face identification, yet it is an area where little research has been done. The objective of face matching is to determine, in real-time, the degree of confidence to which a live subject matches a facial image. Applications for face matching include video surveillance, determination of identification credentials, computer-human interfaces, and communications security.

The method proposed here employs principal component analysis [16] to create a method of face matching which is both computationally efficient and accurate. This method is integrated into a real time system that is based upon a two camera setup. It is able to scan the room, detect faces, and zoom in for a high quality capture of the facial features. The image capture is used in a face matching process to determine if the person found is the desired target. The performance of the system is analyzed based upon the matching accuracy for 10 unique subjects.

Library of Congress Subject Headings

Human face recognition (Computer science); Principal components analysis; Computer vision; Pattern recognition systems

Publication Date

6-2006

Document Type

Thesis

Student Type

Graduate

Degree Name

Computer Engineering (MS)

Department, Program, or Center

Computer Engineering (KGCOE)

Advisor

Andreas Savakis

Advisor/Committee Member

Shanchieh Jay Yang

Advisor/Committee Member

Muhammad Shaaban

Comments

Physical copy available from RIT's Wallace Library at TA1650 .M85 2006

Campus

RIT – Main Campus

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