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Drowsy Status Monitoring System based on Face Feature Analysis

Authors
Jeong, MinguKim, DohunPark, SanghyunPaik, 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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Paik, Joon Ki
첨단영상대학원 (영상학과)
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