Comparative Analysis of Vehicle-Based and Driver-Based Features for Driver Drowsiness Monitoring by Support Vector Machines
Author:
Affiliation:
1. Mercedes-Benz Cars Development Department, Mercedes-Benz AG, Sindelfingen, Germany
2. Department of Human–Computer Interaction, University of Tübingen, Tübingen, Germany
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Science Applications,Mechanical Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/6979/9972869/09929437.pdf?arnumber=9929437
Reference59 articles.
1. Camera-based Driver Drowsiness State Classification Using Logistic Regression Models
2. The detection of drowsiness using a driver monitoring system
3. Data Fusion to Develop a Driver Drowsiness Detection System with Robustness to Signal Loss
4. Fusion of Optimized Indicators from Advanced Driver Assistance Systems (ADAS) for Driver Drowsiness Detection
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