Full metadata
Title
An Analysis of the Usability of Face ID
Description
Since its introduction to the iPhone X in 2017, Apple’s Face ID has been regarded as more accurate than facial recognition systems used by their competitors due to the use of depth information and infrared images to capture accurate face data. The goal of this thesis is to explore the usability of current smartphone facial recognition systems as represented by the latest generation of Apple’s Face ID. To that end, a research study was conducted to test the usability of Apple’s Face ID on the iPhone XR under diverse, simulated conditions designed to replicate real-life scenarios under which a consumer may need to use Face ID. The goal of the study was to make observations on Face ID usability and create a preliminary understanding of areas in which technology may struggle and/or fail. From the results of the research study, Face ID on the iPhone XR generally performed well under low-light conditions and adapted to minor changes in the conditions under which a face capture is done, but did not do as well when the user did not maintain full eye contact with the camera or when the capture is done at an angle.
Date Created
2019-12
Contributors
- Tang, Xina (Author)
- Bazzi, Rida (Thesis director)
- Ulrich, Jon (Committee member)
- Computer Science and Engineering Program (Contributor)
- School of Mathematical and Statistical Sciences (Contributor)
- Barrett, The Honors College (Contributor)
Topical Subject
Resource Type
Extent
38 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Series
Academic Year 2019-2020
Handle
https://hdl.handle.net/2286/R.I.55183
Level of coding
minimal
Cataloging Standards
System Created
- 2019-11-25 11:00:04
System Modified
- 2021-08-11 04:09:57
- 3 years 2 months ago
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