scholarly journals Driver Drowsiness Detection using Machine Learning with Visual Behaviour

2021 ◽  
Vol 9 (VI) ◽  
pp. 1800-1805
Author(s):  
Shivanand Phulari
Keyword(s):  
Machine Learning ◽  
Facial Expressions ◽  
Video Processing ◽  
Road Safety ◽  
Traffic Accident ◽  
Driving Experience ◽  
Driver Drowsiness ◽  
Machine Learning Methods ◽  
Visual Behaviour ◽  
Basic Characteristics

A person while driving a vehicle - if does not have proper sleep or rest, is more inclined to fall asleep which may cause a traffic accident. This is why a system is required which will detect the drowsiness of the driver. Recently, in research and development, machine learning methods have been used to predict a driver's conditions. Those conditions can be used as information that will improve road safety. A driver's condition can be estimated by basic characteristics age, gender and driving experience. Also, driver's driving behaviours, facial expressions, bio-signals can prove helpful in the estimation. Machine Learning has brought progression in video processing which enables images to be analysed with accuracy. In this paper, we proposed a method for detecting drowsiness by using convolution neural network model over position of eyes and extracting detailed features of the mouth using OpenCV and Dlib to count the yawning.

Face Detection and Recognition Using OpenCV

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
Ramadan TH. Hasan ◽  
◽  
Amira Bibo Sallow ◽  
Keyword(s):  
Machine Learning ◽  
Computer Vision ◽  
Facial Expressions ◽  
Face Detection ◽  
Video Processing ◽  
Recognition Of Facial Expressions ◽  
Image And Video Processing ◽  
Gender And Age ◽  
Face Detection And Recognition ◽  
Detection And Recognition

Intel's OpenCV is a free and open-access image and video processing library. It is linked to computer vision, like feature and object recognition and machine learning. This paper presents the main OpenCV modules, features, and OpenCV based on Python. The paper also presents common OpenCV applications and classifiers used in these applications like image processing, face detection, face recognition, and object detection. Finally, we discuss some literary reviews of OpenCV applications in the fields of computer vision such as face detection and recognition, or recognition of facial expressions such as sadness, anger, happiness, or recognition of the gender and age of a person.

scholarly journals Expression Invariant Features for Face Recognition

2019 ◽  
Vol 9 (2) ◽  
pp. 2012-2016
Keyword(s):  
Machine Learning ◽  
Face Recognition ◽  
Facial Expression ◽  
Facial Expressions ◽  
Personal Computer ◽  
The Other ◽  
Machine Learning Methods ◽  
Face Images ◽  
Invariant Features ◽  
The Face

Personal Computer sourced Face Recognition has been a sophisticated and well-found technique which is being rationally utilized for most of the authenticated cases. In reality, there is a number of situations where the expressions of the face will be different. We are here able to instinctively detect the five universal expressions: smile, sadness, anger, surprise, neutral by studying face geometry by determining which type of facial expression has been carried out. Using some facial data with variant expressions. We hereby made some experimentations to calculate the accuracies of some machine learning methods by making some changes in the face images such as a change in expressions, which at last needed for training and recognition identifiers. Our objective is to take the features of neutral facial expressions and add them with the other expressive face images like smiling, angry, sadness to improve the accuracy.

The Characteristics of Traffic Accident Perpetrators in China and Countermeasure Analysis

2013 ◽  
Vol 409-410 ◽  
pp. 1047-1052
Author(s):  
Jun Jun Zou ◽  
Chuan Jiao Sun
Keyword(s):  
Traffic Safety ◽  
Road Safety ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Human Factor ◽  
Safety Education ◽  
Driving Experience ◽  
Main Factors

In the context of rapid increase in car drivers and all citizens being drivers, the driving experience of traffic accident perpetrators has showed a shorter trend. The driver is an important factor that influences the traffic accident, and the drivers behaviors such as speeding, driving on wrong lane and others are the main factors causing traffic accidents. As for the human factor influencing the traffic safety, it is very important to conduct road safety education and publicity work.

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