Computer Vision-Based Drowsiness Detection Using Handcrafted Feature Extraction for Edge Computing Devices
Drowsy driving contributes to over 6000 fatal incidents annually in the US, underscoring the need for effective, non-intrusive drowsiness detection. This study seeks to address detection challenges, particularly in non-standard head positions. Our innovative approach leverages computer vision by com...
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Main Authors: | Valerius Owen, Nico Surantha |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
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Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/15/2/638 |
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