Full metadata
Title
irRotate - Automatic Screen Rotation Based on Face Orientation using Infrared Cameras
Description
This work solves the problem of incorrect rotations while using handheld devices.Two new methods which improve upon previous works are explored. The first method
uses an infrared camera to capture and detect the user’s face position and orient the
display accordingly. The second method utilizes gyroscopic and accelerometer data
as input to a machine learning model to classify correct and incorrect rotations.
Experiments show that these new methods achieve an overall success rate of 67%
for the first and 92% for the second which reaches a new high for this performance
category. The paper also discusses logistical and legal reasons for implementing this
feature into an end-user product from a business perspective. Lastly, the monetary
incentive behind a feature like irRotate in a consumer device and explore related
patents is discussed.
uses an infrared camera to capture and detect the user’s face position and orient the
display accordingly. The second method utilizes gyroscopic and accelerometer data
as input to a machine learning model to classify correct and incorrect rotations.
Experiments show that these new methods achieve an overall success rate of 67%
for the first and 92% for the second which reaches a new high for this performance
category. The paper also discusses logistical and legal reasons for implementing this
feature into an end-user product from a business perspective. Lastly, the monetary
incentive behind a feature like irRotate in a consumer device and explore related
patents is discussed.
Date Created
2020
Contributors
- Tallman, Riley (Author)
- Yang, Yezhou (Thesis advisor)
- Liang, Jianming (Committee member)
- Chen, Yinong (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
52 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.I.62936
Level of coding
minimal
Note
Masters Thesis Computer Science 2020
System Created
- 2021-01-14 09:14:54
System Modified
- 2021-08-26 09:47:01
- 3 years 2 months ago
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