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In this work an online method for camera-based heart rate detection, also known as Photoplethysmography Imaging (PPGI), is presented. The pulse related signal is obtained from RGB videos of the human face, using an off the shelf camera under ambient light conditions. The algorithm for heart rate estimation is based on the beat-to-beat analysis of the PPGI signal, allowing the estimation of psychophysiological...
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...
In the paper, a near-infrared-ray (NIR) and side-view video based low-complexity drowsy driver detection system is developed for day and night applications. The proposed system detects drowsy conditions effectively whether or not glasses. To reduce the redundant computations, the pre-defined ROI (region of interest) is used at the procedures of face, glasses bridge, eyes, and nose feature detections...
This paper focuses on applying human postures and face tracking technologies to design an autonomous patrol vehicle control system, which contains a wireless video surveillance ability. The entire system includes the following several parts: (1) Obtaining the skeleton joints based on the Kinect skeleton tracking: the angles and distances between each human arm's joint are calculated to be the input...
Driver inattention is thought to cause many automobile crashes. Therefore, it is really important to pay high attention all the time though, for one split second of distraction can result in a terrible accident. However, developing an automatic driver assistance system for monitoring his/her attention during driving is a challenging task in computer vision. Level of attention of the driver may vary...
Drowsiness is a major cause of accidents, in particular in road transportation. It is thus crucial to develop robust drowsiness monitoring systems. There is a widespread agreement that the best way to monitor drowsiness is by closely monitoring symptoms of drowsiness that are directly linked to the physiology of an operator such as a driver. The best systems are completely transparent to the operator...
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...
The paper proposed a model using real time driving front video recording to detect driver drowsiness. The video recordings were fed into the TRW's simulator to obtain the lane-related signals. Time domain features and frequency domain features were extracted from the lane-related signals to characterize the difference of alert state and drowsiness state. Both support vector machine and neural network...
A non-intrusive computer vision based ideas has been utilized for the development of a Drowsy Driver Detection System. The small camera has been used by system that focuses straight towards the face of driver and checks the driver's eyes with a specific end goal to recognize fatigue. A warning sign is issued to caution the driver, in such situation when fatigue is recognized. This paper illustrates...
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,...
Data exchange between vehicles and base stations may contain information on traffic accidents, traffic jams, road constructions etc. Risks to data privacy in vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) systems need be minimized. We present a policybased solution that provides controlled and privacypreserving dissemination of video data in V2V and V2I. This policy-based solution relies...
Variations in illumination negatively impacts the performance of most face recognition systems. This is substantially exacerbated when the illumination on a face exhibits strong shadows or other anomalies. This paper describes a system of practical technologies to implement an illumination robust, consumer grade biometric system based on face recognition to be used in the automotive market. It addresses...
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...
Despite the large and spectacular development in the field of vehicle safety, particularly in the context of driver safety needs, solutions remain insufficient and independent. In this paper, we propose a new system that has been dubbed 3SD "Security and Surveillance System for Drivers". It is a multifunction system as a complete package based on intelligent sensors and cameras that constantly...
This paper presents an approach to a driver assistant system for a two-wheeled self-balancing mobility vehicles in particular for a Segway. The approach is aimed for the readily available mobile devices, which become a part of our daily life such as a smartphone or a tablet. If a mobile device is well-positioned on a mobility vehicle, its front and rear cameras can be utilized as sensors to capture...
This paper describes an illumination and pose invariant face recognition system that is intended to be used in the automotive market for vehicle personalization. Near-infrared frame differencing improves the robustness to the outdoor illumination conditions. And we introduce the video-based recognition with pose clustering for pose invariant face recognition. We have collected large video dataset...
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...
It is dangerous for drivers to make a call while driving, as it could easily divert the drivers' attention. In this paper, we present a novel method to detect the driver use of mobile phone based on an in-car camera. The in-car camera is mounted on the front windshield to capture the video of the driver during driving, and an activity parsing algorithm is employed to identify whether the driver is...
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...
Analysis of driver's head behavior is an integral part of driver monitoring system. Driver's coarse gaze direction or gaze zone is a very important cue in understanding driver-state. Many existing gaze zone estimators are, however, limited to single camera perspectives, which are vulnerable to occlusions of facial features from spatially large head movements away from the frontal pose. Non-frontal...
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