Driver drowsiness detection using behavioral measures and machine learning techniques: A review of state-of-art techniques

Mkhuseki Ngxande, Jules-Raymond Tapamo, Michael Burke

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

This paper presents a literature review of driver drowsiness detection based on behavioral measures using machine learning techniques. Faces contain information that can be used to interpret levels of drowsiness. There are many facial features that can be extracted from the face to infer the level of drowsiness. These include eye blinks, head movements and yawning. However, the development of a drowsiness detection system that yields reliable and accurate results is a challenging task as it requires accurate and robust algorithms. A wide range of techniques has been examined to detect driver drowsiness in the past. The recent rise of deep learning requires that these algorithms be revisited to evaluate their accuracy in detection of drowsiness. As a result, this paper reviews machine learning techniques which include support vector machines, convolutional neural networks and hidden Markov models in the context of drowsiness detection. Furthermore, a
meta-analysis is conducted on 25 papers that use machine learning techniques for drowsiness detection. The analysis reveals that support vector machine technique is the most commonly used technique to detect drowsiness, but convolutional neural networks performed better than the other two techniques. Finally, this paper lists publicly available datasets that can be used as benchmarks for drowsiness detection.
Original languageEnglish
Title of host publication2017 Pattern Recognition Association of South Africa and Robotics and Mechatronics
Place of PublicationBloemfontein, South Africa
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages156-161
Number of pages6
ISBN (Electronic)978-1-5386-2314-5
ISBN (Print)978-1-5386-2315-2
DOIs
Publication statusPublished - 18 Jan 2018
EventSymposium of the Pattern Recognition Association of South Africa (PRASA) and Conference of Robotics and Mechatronics (RobMech) - Bloemfontein, South Africa
Duration: 29 Nov 20171 Dec 2017

Conference

ConferenceSymposium of the Pattern Recognition Association of South Africa (PRASA) and Conference of Robotics and Mechatronics (RobMech)
Abbreviated titlePRASA-RobMech 2017
Country/TerritorySouth Africa
CityBloemfontein
Period29/11/171/12/17

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