BROWSE
Detail
Conference Paper
Real-time Drowsiness Detection Algorithm for Driver State Monitoring Systems
Cited 50 time in 
Share 
Share
- Authors
- Jang Woon Baek, Byung-Gil Han, Kwang-Ju Kim, Yun-Su Chung, Soo-In Lee
- Issue Date
- 2018-07
- Citation
- International Conference on Ubiquitous and Future Networks (ICUFN) 2018, pp.73-75
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- In this paper, we proposes a novel drowsiness detection algorithm using a camera near the dashboard. The proposed algorithm detects the driver's face in the image and estimates the landmarks in the face region. In order to detect the face, the proposed algorithm uses an AdaBoost classifier based on the Modified Census Transform features. And the proposed algorithm uses regressing Local Binary Features for face landmark detection. Eye states (closed, open) is determined by the value of Eye Aspect Ratio which is easily calculated by the landmarks in eye region. The proposed algorithm provides realtime performance that can be run on the embedded device. We obtained the dataset using video records from the infrared camera which is used the real-field. The proposed algorithm tested in the target board (i.mx6q). The result shows that the proposed algorithm outperformed in the speed and accuracy.
- KSP Keywords
- AdaBoost Classifier, Binary features, Census Transform, Detection algorithm, Driver state, Drowsiness Detection, Face landmark detection, Infrared camera, Monitoring system, Real-time performance, State monitoring