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Eastern Washington University

3D Image Acquisition System for Facial Recognition

Abstract

dc:description.abstract

<p>Identification of an individual has been a long standing problem in human existence. It is clear from the rising rates of identity theft and misappropriation of services that current methods employed to identify individuals is ineffectual. The most common way people identify other individuals is via recognition of the subjects face. The speed and accuracy with which one person can identify another person is uncanny leading to the development automated facial recognition systems. The vast majority of these systems use two-dimensional (2D) images imagery to perform facial recognition with limited success. The use of 2D imagery has limitations which cannot be overcome therefore three-dimensional (3D) facial recognition systems have become the focus of study. The imaging systems used to capture 3D facial imagery is complex, expensive and requires a degree of cooperation from the subject. This paper proposes the use of older photogrammetry techniques to capture 3D facial imagery thereby eliminating the need for specialized 3D imaging equipment. In addition the camera system, once configured, does not require an operator nor does it require undo cooperation of the subject.</p>

Degree

thesis:*
Name thesis:degree_name
Master of Science (MS) in Computer Science
Level thesis:degree_level
Thesis
Discipline thesis:degree_discipline
Computer Science
Year
2014

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Pearson, James E.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • Access is available to all users

Identifiers

dc:identifier.*
Repository record dc:identifier
https://dc.ewu.edu/theses/256
OAI identifier oai:identifier
oai:dc.ewu.edu:theses-1256

Chain of custody

source
Harvested from
Eastern Washington University
Base URL
dc.ewu.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Pearson, James E.. 3D Image Acquisition System for Facial Recognition. Thesis thesis, 2014. https://dc.ewu.edu/theses/256