Visual recognition of driver hand-held cell phone use based on hidden CRF, Proceedings of 2011 IEEE International Conference on Vehicular Electronics and Safety, pp.10-12, 2011. ,
DOI : 10.1109/ICVES.2011.5983823
Driver Cell Phone Usage Detection from HOV/HOT NIR Images, 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp.23-28, 2014. ,
DOI : 10.1109/CVPRW.2014.42
A Pattern Recognition System for Detecting Use of Mobile Phones While Driving, 2014. ,
DOI : 10.1109/ijcnn.2016.7727803
A machine learning approach for detecting cell phone usage, Proceedings of the IS&T/SPIE Electronic Imaging, International Society for Optics and Photonics, 2015. ,
DOI : 10.1117/12.2083126
Driver cell phone usage detection on Strategic Highway Research Program (SHRP2) face view videos, 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp.7-12, 2015. ,
DOI : 10.1109/CVPRW.2015.7301397
A psychophysiological investigation of the effects of driving longer-combination vehicles, Ergonomics, vol.26, issue.5, pp.581-592, 1998. ,
DOI : 10.1080/00140137808931717
Real-time non-rigid driver head tracking for driver mental state estimation, 2004. ,
Sensors for driver monitoring: current limitations and towards new sensor concepts, Presented at the European Congress on Intelligent Transportation Systems and Services, 4th, 2004. ,
On-road experiment for collecting driving behavioural data of sleepy drivers, pp.259-267, 2007. ,
Real-Time System for Monitoring Driver Vigilance, IEEE Transactions on Intelligent Transportation Systems, vol.7, issue.1, pp.63-77869598, 2006. ,
DOI : 10.1109/TITS.2006.869598
URL : http://www.robesafe.com/personal/bergasa/papers/IEEETITS2006.pdf
Integrated systems. Results of experimental tests, recommendations for introduction, Report Deter, 1995. ,
The use of psychophysiology to assess driver status, Ergonomics, vol.26, issue.9, 1993. ,
DOI : 10.1080/00140138108559234
Traditional and raw task load index (TLX) correlations: are paired comparisons necessary? Paper presented at the International Industrial Ergonomics and Safety Conference, 1989. ,
Novice riders and the predictors of riding without motorcycle protective clothing, Accident Analysis & Prevention, vol.43, issue.3, pp.1095-1103, 2011. ,
DOI : 10.1016/j.aap.2010.12.018
Evaluating feature selection for stress identification, 2012 IEEE 13th International Conference on Information Reuse & Integration (IRI), pp.584-591, 2012. ,
DOI : 10.1109/IRI.2012.6303062
The Measurement of Drivers' Mental Workload, 1996. ,
Driver state monitor from delphi, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.20-25, 2005. ,
Spectral analysis of heart rate variability as an indicator of driver fatigue, Ergonomics, vol.40, issue.7, pp.663-672, 1982. ,
DOI : 10.1037/h0058044
L' integration de systemes electroniques dans la voiture su XXI siècle. Cepadues Editions, 1995. ,
The New Biotechnological Frontier: The Empath Watch, 2011. ,
Driver distraction using visualbased sensors and algorithms, Sensors, issue.11, pp.16-1805, 2016. ,
A comparison of heart rate, eye activity, EEG and subjective measures of pilot mental workload during flight, Aviation Space and Environmental Medicine, vol.69, issue.4, pp.360-367, 1998. ,
Das Lidschlussverhalten als Indikator für Aufmerksamkeits-und Müdigkeitsprozesse bei Arbeitshandlungen, VDI-Gesellschaft Fahrzeug-und Verkehrstechnik (Hrsg.), 2003. ,
Detecting Stress During Real-World Driving Tasks Using Physiological Sensors, IEEE Transactions on Intelligent Transportation Systems, vol.6, issue.2, pp.156-166, 2005. ,
DOI : 10.1109/TITS.2005.848368
URL : http://www.hpl.hp.com/techreports/2004/HPL-2004-229.pdf
Measuring Subjective Workload: When Is One Scale Better Than Many?, Human Factors: The Journal of the Human Factors and Ergonomics Society, vol.35, issue.4, pp.579-601, 1993. ,
DOI : 10.21236/ADA289493
Comparison of Four Subjective Workload Rating Scales, Human Factors: The Journal of the Human Factors and Ergonomics Society, vol.23, issue.2, pp.429-439, 1992. ,
DOI : 10.1037/e574142012-002
Driver drowsiness detection with eyelid related parameters by Support Vector Machine, Expert Systems with Applications, vol.36, issue.4, pp.7651-7658, 2009. ,
DOI : 10.1016/j.eswa.2008.09.030
Hands and Arms Motion Estimation of a Car Driver with Depth Image Sensor by Using Particle Filter, Soft Computing in Machine Learning, Advances in Intelligent Systems and Computing, pp.75-84, 2014. ,
DOI : 10.1007/978-3-319-05533-6_8
Facial expression analysis for predicting unsafe driving behavior, IEEE Pervasive Computing, vol.10, issue.4, pp.84-95, 2010. ,
DOI : 10.1109/MPRV.2010.46
Automobile driver' s stress index provision system that utilizes electrocardiogram Intelligent Vehicles Symposium, IEEE, pp.652-656, 2007. ,
DOI : 10.1109/ivs.2007.4290190
Real-Time Eye, Gaze, and Face Pose Tracking for Monitoring Driver Vigilance, Real-Time Imaging, vol.8, issue.5, pp.357-3770279, 2002. ,
DOI : 10.1006/rtim.2002.0279
URL : http://www.ecse.rpi.edu/homepages/qji/Papers/realtime_eye_gaze_driver_vigilance.pdf
Real-Time Nonintrusive Monitoring and Prediction of Driver Fatigue, IEEE Transactions on Vehicular Technology, vol.53, issue.4, 2004. ,
DOI : 10.1109/TVT.2004.830974
URL : http://www.ecse.rpi.edu/~qji/Papers/IEEE_vt.pdf
A New Method for Monitoring the Drowsiness of the Drivers, International Conference on Fatigue Management in Transportation Operations, pp.132-187, 2005. ,
The Classification of Valid and Invalid Beats of Three-Dimensional Nystagmus Eye Movement Signals Using Machine Learning Methods, Advances in Artificial Neural Systems, vol.2012, issue.3 ,
DOI : 10.3233/ICA-2011-0385
Driver behavior analysis through speech emotion understanding, 2010 IEEE Intelligent Vehicles Symposium, pp.2010-238, 2010. ,
DOI : 10.1109/IVS.2010.5548124
Toward Emotion Recognition in Car-Racing Drivers: A Biosignal Processing Approach, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, vol.38, issue.3, pp.502-512918624, 2008. ,
DOI : 10.1109/TSMCA.2008.918624
Non-intrusive car driver's emotion recognition using thermal camera, Proceedings of the Joint INDS'11 & ISTET'11, p.2011, 2011. ,
DOI : 10.1109/INDS.2011.6024802
A 3D experimental framework for exploring drivers' body activity using infrared depth sensors, 2013 International Conference on Connected Vehicles and Expo (ICCVE), pp.2013-574, 2013. ,
DOI : 10.1109/ICCVE.2013.6799857
Fuzzy Evaluation of Heart Rate Signals for Mental Stress Assessment, IEEE Transactions on Fuzzy Systems, vol.15, issue.5, pp.791-808, 2007. ,
DOI : 10.1109/TFUZZ.2006.889825
Subjective sleepiness, simulated driving performance and blink duration: examining individual differences, Journal of Sleep Research, vol.27, issue.2, pp.47-53, 2006. ,
DOI : 10.1016/0013-4694(87)90096-4
Development of facial-direction detection sensor, Proceedings of the 13th Its World Congress, pp.8-12 ,
An Experimental Study on Physiological Parameters Toward Driver Emotion Recognition, Ergonomics and Health Aspects of Work with Computers, pp.237-246, 2007. ,
DOI : 10.1007/978-3-540-73333-1_30
Using Kinect for face recognition under varying poses, expressions, illumination and disguise, 2013 IEEE Workshop on Applications of Computer Vision (WACV), pp.2013-186, 2013. ,
DOI : 10.1109/WACV.2013.6475017
URL : http://www.csse.uwa.edu.au/~ajmal/papers/billy_wacv_13.pdf
An Intelligent Noninvasive Sensor for Driver Pulse Wave Measurement, IEEE Sensors Journal, vol.7, issue.5, pp.790-799, 2007. ,
DOI : 10.1109/JSEN.2007.894923
Thermal and cardiovascular strain imposed by motorcycle protective clothing under Australian summer conditions, Ergonomics, vol.594, pp.504-513, 2016. ,
Pilot plans, tools and evaluation methodology, 2009. ,
The production and recognition of emotions in speech: features and algorithms, International Journal of Human-Computer Studies, vol.59, issue.1-2, pp.157-183, 2003. ,
DOI : 10.1016/S1071-5819(02)00141-6
URL : http://www.pyoudeyer.com/emotionsIJHCS.pdf
Interval level measurement with visual analogue scales in Internetbased research, 2008. ,
DOI : 10.3758/brm.40.3.699
URL : http://www.zora.uzh.ch/id/eprint/4565/2/ReipsFunke%28uncorr_proofs%29mit_Notizen.pdf
A reasoning-based framework for car driver's stress prediction, 16th Mediterranean Conference on, pp.627-632, 2008. ,
DOI : 10.1109/med.2008.4602162
Robot, you can drive my car, IEEE Spectrum, vol.51, issue.6, pp.60-90, 2014. ,
DOI : 10.1109/MSPEC.2014.6821623
Estimating aircrew fatigue: A technique with implications to airlift operations . Brooks AFB, TX : USAF School of Aerospace Medicine ,
Personalized Stress Detection from Physiological Measurements, International Symposium on Quality of Life Technology, 2010. ,
An active driver fatigue identification technique using multiple physiological features, 2011 International Conference on Mechatronic Science, Electric Engineering and Computer (MEC), pp.733-737 ,
DOI : 10.1109/MEC.2011.6025569
Keep Your Eyes on the Road: Young Driver Crash Risk Increases According to Duration of Distraction, Journal of Adolescent Health, vol.54, issue.5, pp.61-67, 2014. ,
DOI : 10.1016/j.jadohealth.2013.11.021
URL : https://doi.org/10.1016/j.jadohealth.2013.11.021
Biosignal Based Discrimination between Slight and Strong Driver Hypovigilance by Support-Vector Machines, In Agents and Artificial Intelligence ,
DOI : 10.1007/978-3-642-11819-7_14
Speech based emotion classification framework for driver assistance system, 2010 IEEE Intelligent Vehicles Symposium, pp.2010-174, 2010. ,
DOI : 10.1109/IVS.2010.5547956
URL : http://cvrr.ucsd.edu/publications/2010/IV10_ATawari.pdf
Classifiers for driver activity monitoring, Transportation Research Part C: Emerging Technologies, vol.15, issue.1, pp.51-67, 2007. ,
DOI : 10.1016/j.trc.2007.01.001
Drowsy Driver Detection Through Facial Movement Analysis, Human?Computer Interaction, Lecture Notes in Computer Science, pp.6-18, 2007. ,
DOI : 10.1007/978-3-540-75773-3_2
Vehicle Integrated Non-Intrusive Monitoring of Driver Biological Signals (SAE Technical Paper No, 1095. ,
DOI : 10.4271/2011-01-1095
Head pose estimation for driver monitoring, IEEE Intelligent Vehicles Symposium. Presented at the 2004 IEEE Intelligent Vehicles Symposium, pp.501-506, 2004. ,