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Automated Face Tracking and Recognition

Title: Automated Face Tracking and Recognition.
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Name(s): Hesher, Matthew Curtis, author
Erlebacher, Gordon, professor directing thesis
Srivastava, Anuj, professor co-directing thesis
Gallivan, Kyle, committee member
Department of Computer Science, degree granting department
Florida State University, degree granting institution
Type of Resource: text
Genre: Text
Issuance: monographic
Date Issued: 2003
Publisher: Florida State University
Place of Publication: Tallahassee, Florida
Physical Form: computer
online resource
Extent: 1 online resource
Language(s): English
Abstract/Description: We have considered the problem of tracking and recognition using a three dimensional representation of human faces. First we present a review of the research in the tracking and recognition fields including a list of several commercially available face tracking and recognition systems. Next, two algorithms are described: one for tracking faces from observed images and one for recognition of faces from observed geometries. The tracking algorithm uses 3D shape and texture of a human face to estimate the changing position and orientation of a real face in a video image sequence. The recognition algorithm uses principal component analysis (PCA) of range images generated from the 3D shape of a human face to create a database of low-dimensional face representations for efficient recognition. Range images are robust to illumination and texture variations and thus avoid some of the current limitations in face recognition.
Identifier: FSU_migr_etd-4074 (IID)
Submitted Note: A Thesis submitted to the Department of Computer Science in partial fulfillment of the requirements for the degree of Master of Science.
Degree Awarded: Summer Semester, 2003.
Date of Defense: April 10, 2003.
Keywords: Face Recognition, Face Tracking
Bibliography Note: Includes bibliographical references.
Advisory Committee: Gordon Erlebacher, Professor Directing Thesis; Anuj Srivastava, Professor Co-Directing Thesis; Kyle Gallivan, Committee Member.
Subject(s): Computer science
Persistent Link to This Record: http://purl.flvc.org/fsu/fd/FSU_migr_etd-4074
Owner Institution: FSU

Choose the citation style.
Hesher, M. C. (2003). Automated Face Tracking and Recognition. Retrieved from http://purl.flvc.org/fsu/fd/FSU_migr_etd-4074