A Head Motion Recognition Approach for Alertness Detection

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

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Detail(s)

Original languageEnglish
Title of host publication2022 IEEE 20th International Conference on Industrial Informatics (INDIN)
PublisherIEEE
Pages245-250
ISBN (Electronic)978-1-7281-7568-3
Publication statusPublished - 2022

Publication series

NameIEEE International Conference on Industrial Informatics (INDIN)
Volume2022-July
ISSN (Print)1935-4576

Conference

Title20th IEEE International Conference on Industrial Informatics (INDIN 2022)
PlaceAustralia
CityPerth
Period25 - 28 July 2022

Abstract

Alertness detection is an important component of systems used to detect driver fatigue in order to prevent road accidents. Various approaches have been proposed in literature, including the use of sensors that track physiological markers and camera based systems that rely on computer vision techniques to track facial markers. In this paper, we adopt liveness detection to determine alertness. Liveness detection is a method used in biometrics to determine if a face, or fingerprint, is from a live person. The results show that the approach is robust to different lighting conditions.

Research Area(s)

  • driver fatigue, head pose, liveness detection

Citation Format(s)

A Head Motion Recognition Approach for Alertness Detection. / Huang, Kam Wing; Silva, Bruno J.; Hancke, Gerhard P.
2022 IEEE 20th International Conference on Industrial Informatics (INDIN). IEEE, 2022. p. 245-250 (IEEE International Conference on Industrial Informatics (INDIN); Vol. 2022-July).

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review