# Drowsiness-Detection
Matlab Code for Drowsiness Detection
A Matlab code is written to moniter the status of a person and sound an alarm in case of drowsiness. i have already trained the SVM classifier with Fatigue and Non Fatigue samples.
How to run??
1. Unzip and place the 'Sleep' folder in the path of Matlab.
2. Turn on your webcam, go to command window and type 'imaqtool' to find the supported adaptors.
3. Open main.m and go to line no. 17 and change the adaptor name to the supported one.
(Usually 'winvideo',1 is supported in all windows versions).
4. Now run main.m
5. Place yourself at a distance such that your face is visible in the window
6. Non Fatigue Status: The default status, appears when your eyes are wide open and mouth is closed
7. Fatigue Status: When eyes are closed and mouth is opened for several seconds, the alarm sounds a beep.
8. Make sure the room is well lit
Note: The model is not trained to work perfectly under dark or very low dim light conditions, I will upload a much better code once I get better results with an efficient set of features.
Cite the following if you are using my work:
[1] Manu, B. N. "Facial features monitoring for real time drowsiness detection." Innovations in Information Technology (IIT), 2016 12th International Conference on. IEEE, 2016.
IEEE Paper Download link: https://www.researchgate.net/publication/315685957_Facial_Features_Monitoring_for_Real_Time_Drowsiness_Detection
PPT Download link: https://www.researchgate.net/publication/315686000_Facial_Features_Monitoring_for_Real_Time_Drowsiness_Detection_PPT
Suggestions and comments are always welcome,
Thanks in advance,
Manu B.N
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MATLAB的疲劳检测代码-Drowsiness-Detection:Matlab睡意检测代码
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m:11个
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2021-05-23
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MATLAB的疲劳检测代码睡意检测 Matlab睡意检测代码 编写Matlab代码以监视人的状态并在睡意时发出警报。 我已经用疲劳和非疲劳样本训练了SVM分类器。 如何运行? 解压缩并将“睡眠”文件夹放置在Matlab的路径中。 打开网络摄像头,转到命令窗口,然后键入“ imaqtool”以找到受支持的适配器。 打开main.m并转到行号。 17,然后将适配器名称更改为支持的名称。 (通常,所有Windows版本都支持'winvideo',1)。 现在运行main.m 将自己放置在一定距离内,以使您的脸在窗口中可见 非疲劳状态:默认状态,当您睁大眼睛并闭上嘴时出现 疲劳状态:闭眼和张开嘴几秒钟时,警报器会发出蜂鸣声。 确保房间光线充足注意:该模型在黑暗或非常暗的光线条件下均未经过训练,无法正常工作,一旦使用一组有效的功能获得更好的结果,我将上传更好的代码。 如果您正在使用我的作品,请引用以下内容: [1] Manu,BN,“用于实时睡意检测的面部特征监视”。 信息技术创新(IIT),2016年第12届国际会议。 IEEE,2016年。 IEEE论文下载链接: PPT下载链接: 总是欢迎
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Drowsiness-Detection-master.zip (19个子文件)
Drowsiness-Detection-master
svm.mat 1KB
trainDB.m 2KB
NF.mat 240B
main.m 5KB
test_Svm.m 197B
feature_extraction_nonfatigue.m 4KB
train_svm.m 601B
FA.mat 241B
match_DB.m 601B
feture_extraction_fatigue.m 4KB
DB.mat 181KB
create_Database.m 3KB
demo_1.m 3KB
main_webcam.m 3KB
code2.zip 704KB
README.md 2KB
skin_seg2.m 530B
ix.mat 174B
Database.zip 522KB
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