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Fast expansion of Advanced Driver Assistance Systems (ADAS) market and applications has resulted in a high demand for various accompanying algorithms. In this paper we present an implementation of Driver monitoring algorithm. Main goal of the algorithm is to automatically asses if driver is tired and in that case, raise a proper alert. It is widely used as a standard component of rest recommendation...
This paper presents a study in which driver's gaze zone is categorized using new deep learning techniques. Since the sequence of gaze zones of a driver reflects precisely what and how he behaves, it allows us infer his drowsiness, focusing or distraction by analyzing the images coming from a camera. A Haar feature based face detector is combined with a correlation filter based MOSS tracker for the...
Extracting driver's facial feature helps to identify the vigilance level of a driver. Some research about facial feature extraction also has been developed for controlled interface of vehicle. To acquire facial feature of drivers, research using various visual sensors have been reported. However, potential challenges to such a work include rapid illumination variation resulting from ambient lights,...
This paper presents a drowsiness detection method for drivers. The drowsiness is detected by monitoring the eye state (open or close). Firstly, the detection of human face and eye regions is performed using the Haar cascade method. We then locate a dark circular object (i.e. the pupil) using two vectors within the eye regions: one is distance vectors and the other gradient vectors. The cross-correlation...
In this paper, we introduce a prototype attention detection system for automotive drivers. The driver is monitored through a Microsoft Kinect camera which provides RGB, depth, and infrared images in order to cover situations in which normal cameras might not achieve good results. The Kinect is connected to a Xilinx ZedBoard wich uses a Zynq-7000 SoC as processing platform. The attention detection...
This paper comes as a response to the fact that, lately, more and more accidents are caused by people who fall asleep at the wheel. Eye tracking is one of the most important aspects in driver assistance systems since human eyes hold much in-formation regarding the driver's state, like attention level, gaze and fatigue level. The number of times the subject blinks will be taken into account for identification...
Due to the high volume of traffic on modern roadways, transportation agencies have proposed High Occupancy Vehicle (HOV) lanes and High Occupancy Tolling (HOT) lanes to promote car pooling. However, enforcement of the rules of these lanes is currently performed by roadside enforcement officers using visual observation. Manual roadside enforcement is known to be inefficient, costly, potentially dangerous,...
Drowsiness and Fatigue of drivers are amongst the significant causes of road accidents. Every year, they increase the amounts of deaths and fatalities injuries globally. In this paper, a module for Advanced Driver Assistance System (ADAS) is presented to reduce the number of accidents due to drivers fatigue and hence increase the transportation safety; this system deals with automatic driver drowsiness...
Driver drowsiness is a major factor in most driving accidents. In this paper we present a robust and intelligent scheme for driver drowsiness detection employing the fusion of eye closure and yawning detection methods. In this approach, the driver's facial appearance is captured via a camera installed in the car. In the first step, the face region is detected and tracked in the captured video sequence...
In this demo we will present a vision-based smart environment using in-car cameras that can be used for real time tracking and monitoring of a driver in order to detect the driver's drowsiness based on yawning detection. As driver fatigue and drowsiness is a major cause behind a large number of road accidents, the assistive systems that monitor a driver's level of drowsiness and alert the driver in...
Several intrusive and non-intrusive techniques have been proposed in the past to monitor car driver's emotions but very little light was shed on using thermal cameras for such applications. This paper details with one such system that uses a single infrared thermal camera. Such a camera was used to overcome the issues pertaining to usage of single audio/visual sensors. Fusion of the outputs with the...
This paper presents a nonintrusive approach for monitoring driver drowsiness, based on computer vision techniques, installed in a realistic driving simulator. An IR stereo camera is placed in from of the driver in order to obtain PERCLOS, the most confident drowsiness parameter [1], in real-time and in a robust and automatic way. Our proposal doesn't need a calibration process and includes three main...
Driver distraction and fatigue are important factors that cause accidents. We developed a novel machine vision system which can provide the driver's face pose and eye status information as well as the driver's viewing scene. The driving original video information was obtained simultaneously by a panoramic annular lens (PAL) camera in the system. The PAL camera can capture its surroundings with a field...
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