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 proceedingConference contribution

59 Downloads (Pure)


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 languageEnglish
Title of host publicationIntelligent Systems and Applications
Subtitle of host publicationProceedings of the 2021 Intelligent Systems Conference (IntelliSys) Volume 1
EditorsKohei Arai
Number of pages10
ISBN (Electronic)9783030821937
ISBN (Print)9783030821920
Publication statusPublished - 4 Aug 2021
EventIntelliSys 2021 - Amsterdam, Netherlands
Duration: 2 Sept 20213 Sept 2021

Publication series

NameLecture Notes in Networks and Systems
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389


ConferenceIntelliSys 2021


  • Camera
  • Face recognition
  • SDK
  • User identification
  • Wheelchair


Dive into the research topics of 'Facial recognition software for identification of powered wheelchair users'. Together they form a unique fingerprint.

Cite this