Drowsy Status Monitoring System based on Face Feature Analysis
- Authors
- Jeong, Mingu; Kim, Dohun; Park, Sanghyun; Paik, Joonki
- Issue Date
- Feb-2022
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- drowsy recognition; DSM; face detection; head pose; landmark detection
- Citation
- 2022 International Conference on Electronics, Information, and Communication, ICEIC 2022
- Journal Title
- 2022 International Conference on Electronics, Information, and Communication, ICEIC 2022
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/58007
- DOI
- 10.1109/ICEIC54506.2022.9748269
- ISSN
- 0000-0000
- Abstract
- With the advancement of autonomous driving technology, a driving status monitoring system gains increasing attraction in the mobility field. In this paper, we present a drowsy driving detection system using intelligent recognition of driving status. The proposed method first detects the driver's face, and then extracts face landmarks for face analysis. Drowsiness driving detection is performed by analyzing the following two characteristics based on the extracted landmarks: i) eye condition analysis based on pupil recognition and ii) head movement analysis based on the head pose. The proposed method used an efficient algorithm for real-time analysis, and the performance of the proposed method was evaluated using in-house datasets. © 2022 IEEE.
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Collections - Graduate School of Advanced Imaging Sciences, Multimedia and Film > Department of Imaging Science and Arts > 1. Journal Articles
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