Facial recognition software for identification of powered wheelchair users

Giles Tewkesbury; Samuel Lifton; Malik Haddad; David Sanders; Alexander Gegov

doi:10.1007/978-3-030-82193-7_42

Facial recognition software for identification of powered wheelchair users

Giles Tewkesbury, Samuel Lifton, Malik Haddad, David Sanders, Alexander Gegov

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

117 Downloads (Pure)

Abstract

The research presented in this paper investigates the use of facial recognition software as a potential system to identify powered wheelchair users. Facial recognition offers advantages over other biometric systems where wheelchair users have disabilities. Facial recognition systems scan an image or video feed
for a face, and compare the detected face to previously detected data. This paper reviews the software development kits and the libraries available for creating such as systems and discusses the technologies chosen to create a prototype facial recognition system. The new prototype system was trained with 262 identification pictures and confidence ratings were produced from the system for video feeds from twelve users. The results from the trials and variance in confidence ratings are discussed with respect to gender, presence of glasses and make up. The results demonstrated the system to be 95% efficient in its ability to identify users.

Original language	English
Title of host publication	Intelligent Systems and Applications
Subtitle of host publication	Proceedings of the 2021 Intelligent Systems Conference (IntelliSys) Volume 1
Editors	Kohei Arai
Publisher	Springer
Pages	630-639
Number of pages	10
ISBN (Electronic)	9783030821937
ISBN (Print)	9783030821920
DOIs	https://doi.org/10.1007/978-3-030-82193-7_42
Publication status	Published - 4 Aug 2021
Event	IntelliSys 2021 - Amsterdam, Netherlands Duration: 2 Sept 2021 → 3 Sept 2021

Publication series

Name	Lecture Notes in Networks and Systems
Volume	294
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	IntelliSys 2021
Country/Territory	Netherlands
City	Amsterdam
Period	2/09/21 → 3/09/21

Keywords

Camera
Face recognition
SDK
User identification
Wheelchair

Access to Document

10.1007/978-3-030-82193-7_42

Giles Intellisys21 - PureAccepted author manuscript (Post-print), 248 KB

Using artificial intelligence to share control of a powered-wheelchair between a wheelchair user and an intelligent sensor system
Sanders, D., Gegov, A. & Haddad, M.
Engineering and Physical Sciences Research Council
1/11/18 → 1/11/22
Project: Research

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Cite this

Tewkesbury, G., Lifton, S., Haddad, M., Sanders, D., & Gegov, A. (2021). Facial recognition software for identification of powered wheelchair users. In K. Arai (Ed.), Intelligent Systems and Applications: Proceedings of the 2021 Intelligent Systems Conference (IntelliSys) Volume 1 (pp. 630-639). (Lecture Notes in Networks and Systems; Vol. 294). Springer. https://doi.org/10.1007/978-3-030-82193-7_42

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abstract = "The research presented in this paper investigates the use of facial recognition software as a potential system to identify powered wheelchair users. Facial recognition offers advantages over other biometric systems where wheelchair users have disabilities. Facial recognition systems scan an image or video feedfor a face, and compare the detected face to previously detected data. This paper reviews the software development kits and the libraries available for creating such as systems and discusses the technologies chosen to create a prototype facial recognition system. The new prototype system was trained with 262 identification pictures and confidence ratings were produced from the system for video feeds from twelve users. The results from the trials and variance in confidence ratings are discussed with respect to gender, presence of glasses and make up. The results demonstrated the system to be 95% efficient in its ability to identify users.",

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Tewkesbury, G, Lifton, S, Haddad, M, Sanders, D & Gegov, A 2021, Facial recognition software for identification of powered wheelchair users. in K Arai (ed.), Intelligent Systems and Applications: Proceedings of the 2021 Intelligent Systems Conference (IntelliSys) Volume 1. Lecture Notes in Networks and Systems, vol. 294, Springer, pp. 630-639, IntelliSys 2021, Amsterdam, Netherlands, 2/09/21. https://doi.org/10.1007/978-3-030-82193-7_42

Facial recognition software for identification of powered wheelchair users. / Tewkesbury, Giles; Lifton, Samuel; Haddad, Malik et al.
Intelligent Systems and Applications: Proceedings of the 2021 Intelligent Systems Conference (IntelliSys) Volume 1. ed. / Kohei Arai. Springer, 2021. p. 630-639 (Lecture Notes in Networks and Systems; Vol. 294).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Tewkesbury, Giles

AU - Lifton, Samuel

AU - Haddad, Malik

AU - Sanders, David

AU - Gegov, Alexander

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PY - 2021/8/4

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N2 - The research presented in this paper investigates the use of facial recognition software as a potential system to identify powered wheelchair users. Facial recognition offers advantages over other biometric systems where wheelchair users have disabilities. Facial recognition systems scan an image or video feedfor a face, and compare the detected face to previously detected data. This paper reviews the software development kits and the libraries available for creating such as systems and discusses the technologies chosen to create a prototype facial recognition system. The new prototype system was trained with 262 identification pictures and confidence ratings were produced from the system for video feeds from twelve users. The results from the trials and variance in confidence ratings are discussed with respect to gender, presence of glasses and make up. The results demonstrated the system to be 95% efficient in its ability to identify users.

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Facial recognition software for identification of powered wheelchair users

Abstract

Publication series

Conference

Keywords

Access to Document

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Projects

Using artificial intelligence to share control of a powered-wheelchair between a wheelchair user and an intelligent sensor system

Cite this