16.7.2.8.2 Driver Monitoring, Eyes, Gaze, Drowsiness

Chapter Contents (Back)
Eye Tracking. Gaze Determination. Gaze Tracking. Drowsiness. Driver Monitoring. Fatigue and Drowsiness share a lot:
See also Driver Fatigue.
See also Driver Distraction Analysis, Driver Attention, Driver Inattention.
See also Gaze Tracking, Gaze Determination.
See also Eye Tracking, Pupil Tracking.
See also Driver Assistance Systems and Techniques. Non eye monitoring:
See also Surveillance of Vehicles and Occupants, Driver Monitoring.

Smart Eye,
1999.
WWW Link. Vendor, Eye Tracking. Vendor, Driver Monitoring. Eye tracking for driver monitoring.

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Ji, Q.A.[Qi-Ang], Yang, X.J.[Xiao-Jie],
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Smith, R.P.[Raymond Paul], Shah, M.[Mubarak], da Vitoria Lobo, N.[Niels],
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Smith, R.P.[Raymond Paul], Shah, M.[Mubarak], da Vitoria Lobo, N.[Niels],
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Healey, J.A.[Jennifer A.], and Picard, R.W.[Rosalind W.],
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Newman, T.J.[Timothy J.], Scharenbroch, G.K.[Gregory K.], Smith, M.R.[Matthew R.], Zhang, H.[Harry], Widmann, G.R.[Glenn R.], Witt, G.J.[Gerald J.],
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Bergasa, L.M., Nuevo, J., Sotelo, M.A., Barea, R., Lopez, M.E.,
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Schreiber, D.[David], Luo, Y.[Yun],
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d'Orazio, T., Leo, M., Guaragnella, C., Distante, A.,
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Cheng, S.Y.[Shinko Y.], Park, S.H.[Sang-Ho], Trivedi, M.M.[Mohan M.],
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McCall, J.C., Wipf, D.P., Trivedi, M.M., Rao, B.D.[Bhaskar D.],
Lane Change Intent Analysis Using Robust Operators and Sparse Bayesian Learning,
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Cheng, S.Y., Trivedi, M.M.,
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Sekizawa, S., Inagaki, S., Suzuki, T., Hayakawa, S., Tsuchida, N., Tsuda, T., Fujinami, H.,
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Katsis, C.D., Katertsidis, N., Ganiatsas, G., Fotiadis, D.I.,
Toward Emotion Recognition in Car-Racing Drivers: A Biosignal Processing Approach,
SMC-A(38), No. 3, May 2008, pp. 502-512.
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Driver Monitoring. BibRef

Steffin, M.[Morris],
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US_Patent7,336,804, Feb 26, 2008
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Skog, I., Handel, P.,
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Giusti, A.[Alessandro], Zocchi, C., Rovetta, A.,
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Malta, L., Miyajima, C., Takeda, K.,
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Doshi, A., Trivedi, M.M.,
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Murphy-Chutorian, E., Trivedi, M.M.,
Head Pose Estimation and Augmented Reality Tracking: An Integrated System and Evaluation for Monitoring Driver Awareness,
ITS(11), No. 2, June 2010, pp. 300-311.
IEEE DOI 1007

See also Particle filtering with rendered models: A two pass approach to multi-object 3D tracking with the GPU. BibRef

Pauwelussen, J., Feenstra, P.J.,
Driver Behavior Analysis During ACC Activation and Deactivation in a Real Traffic Environment,
ITS(11), No. 2, June 2010, pp. 329-338.
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Perez, A., Garcia, M.I., Nieto, M., Pedraza, J.L., Rodriguez, S., Zamorano, J.,
Argos: An Advanced In-Vehicle Data Recorder on a Massively Sensorized Vehicle for Car Driver Behavior Experimentation,
ITS(11), No. 2, June 2010, pp. 463-473.
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Lee, S.J., Jo, J., Jung, H.G., Park, K.R., Kim, J.,
Real-Time Gaze Estimator Based on Driver's Head Orientation for Forward Collision Warning System,
ITS(12), No. 1, March 2011, pp. 254-267.
IEEE DOI 1103
For driver monitoring. BibRef

Malta, L., Miyajima, C., Kitaoka, N., Takeda, K.,
Analysis of Real-World Driver's Frustration,
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Sandberg, D., Akerstedt, T., Anund, A., Kecklund, G., Wahde, M.,
Detecting Driver Sleepiness Using Optimized Nonlinear Combinations of Sleepiness Indicators,
ITS(12), No. 1, March 2011, pp. 97-108.
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Jabon, M.E.[Maria E.], Ahn, G.[Grace], Bailenson, J.N.[Jeremy N.],
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Track driver features, predict accidents. BibRef

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Elsevier DOI 1201
Gesture analysis; Hidden Markov Models; Optical flow; Intelligent Driver Assistance; Active safety; Accident prevention; Pedal misapplications; Foot tracking; Intelligent vehicle BibRef

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Ahlstrom, C., Victor, T., Wege, C., Steinmetz, E.,
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Wang, K.F.[Kun-Feng], Huang, W.L.[Wu-Ling], Tian, B.[Bin], Wen, D.[Ding],
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Metaxas, D.N.[Dimitris N.], Zhang, S.T.[Shao-Ting],
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Tawari, A.[Ashish], Martin, S.[Sujitha], Trivedi, M.M.[Mohan M.],
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Ohn-Bar, E.[Eshed], Trivedi, M.M.[Mohan M.],
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Ohn-Bar, E.[Eshed], Martin, S.[Sujitha], Tawari, A.[Ashish], Trivedi, M.M.[Mohan M.],
Head, Eye, and Hand Patterns for Driver Activity Recognition,
ICPR14(660-665)
IEEE DOI 1412
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Wu, B.F.[Bing-Fei], Chen, Y.H.[Ying-Han], Yeh, C.H.[Chung-Hsuan],
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Olaverri-Monreal, C., Hasan, A.E., Bulut, J., Korber, M., Bengler, K.,
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Shirazi, M.M., Rad, A.B.,
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IEEE DOI 1410
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Pelaez C, G.A., Garcia, F., de la Escalera, A.[Arturo], Armingol, J.M.,
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ITS(15), No. 4, August 2014, pp. 1855-1860.
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Narayanan, A., Kaimal, R.M., Bijlani, K.,
Yaw Estimation Using Cylindrical and Ellipsoidal Face Models,
ITS(15), No. 5, October 2014, pp. 2308-2320.
IEEE DOI 1410
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Narayanan, A., Kaimal, R.M., Bijlani, K.,
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ITS(17), No. 12, December 2016, pp. 3446-3460.
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Resalat, S.N.[Seyed Navid], Saba, V.[Valiallah],
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Akrout, B.[Belhassen], Mahdi, W.[Walid],
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Taniguchi, T., Nagasaka, S., Hitomi, K., Takenaka, K., Bando, T.,
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Taniguchi, T., Furusawa, K., Liu, H., Tanaka, Y., Takenaka, K., Bando, T.,
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Taniguchi, T., Nagasaka, S., Hitomi, K., Chandrasiri, N.P., Bando, T., Takenaka, K.,
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Vicente, F., Huang, Z., Xiong, X., de la Torre, F.[Fernando], Zhang, W., Levi, D.,
Driver Gaze Tracking and Eyes Off the Road Detection System,
ITS(16), No. 4, August 2015, pp. 2014-2027.
IEEE DOI 1508
Cameras BibRef

Balsa-Barreiro, J., Valero-Mora, P.M., Pareja-Montoro, I., Sánchez-García, M.,
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Alioua, N.[Nawal], Amine, A.[Aouatif], Bensrhair, A.[Abdelaziz], Rziza, M.[Mohammed],
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IJCVR(5), No. 4, 2015, pp. 347-364.
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Wahlstrom, J., Skog, I., Handel, P.,
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Rodrigues, J.G.P., Kaiseler, M., Aguiar, A., Silva Cunha, J.P., Barros, J.,
A Mobile Sensing Approach to Stress Detection and Memory Activation for Public Bus Drivers,
ITS(16), No. 6, December 2015, pp. 3294-3303.
IEEE DOI 1512
Biomedical monitoring BibRef

Bender, A., Agamennoni, G., Ward, J.R., Worrall, S., Nebot, E.M.,
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Bayes methods BibRef

Olivari, M., Nieuwenhuizen, F.M., Venrooij, J., Bulthoff, H.H., Pollini, L.,
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Cyber(45), No. 12, December 2015, pp. 2780-2791.
IEEE DOI 1512
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Artan, Y.[Yusuf], Bulan, O.[Orhan], Loce, R.P.[Robert P.], Paul, P.[Peter],
Passenger Compartment Violation Detection in HOV/HOT Lanes,
ITS(17), No. 2, February 2016, pp. 395-405.
IEEE DOI 1602
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Earlier:
Driver Cell Phone Usage Detection from HOV/HOT NIR Images,
PBVS14(225-230)
IEEE DOI 1409
Automotive components. cell phone usage detection;image classification BibRef

Wshah, S., Xu, B., Bulan, O., Kumar, J., Paul, P.,
Deep learning architectures for domain adaptation in HOV/HOT lane enforcement,
WACV16(1-7)
IEEE DOI 1606
Cameras BibRef

Li, N., Busso, C.,
Detecting Drivers' Mirror: Checking Actions and Its Application to Maneuver and Secondary Task Recognition,
ITS(17), No. 4, April 2016, pp. 980-992.
IEEE DOI 1604
Feature extraction BibRef

Fridman, L., Langhans, P., Lee, J., Reimer, B.,
Driver Gaze Region Estimation without Use of Eye Movement,
IEEE_Int_Sys(31), No. 3, May 2016, pp. 49-56.
IEEE DOI 1606
Feature extraction BibRef

Fridman, L., Lee, J., Reimer, B., Victor, T.,
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IET-CV(10), No. 4, 2016, pp. 308-313.
DOI Link 1608
driver information systems BibRef

Deng, T., Yang, K., Li, Y., Yan, H.,
Where Does the Driver Look? Top-Down-Based Saliency Detection in a Traffic Driving Environment,
ITS(17), No. 7, July 2016, pp. 2051-2062.
IEEE DOI 1608
intelligent transportation systems BibRef

Lundgren, M., Hammarstrand, L., McKelvey, T.,
Driver-Gaze Zone Estimation Using Bayesian Filtering and Gaussian Processes,
ITS(17), No. 10, October 2016, pp. 2739-2750.
IEEE DOI 1610
Cameras BibRef

Aghaei, A.S., Donmez, B., Liu, C.C., He, D., Liu, G., Plataniotis, K.N., Chen, H.Y.W., Sojoudi, Z.,
Smart Driver Monitoring: When Signal Processing Meets Human Factors: In the driver's seat,
SPMag(33), No. 6, November 2016, pp. 35-48.
IEEE DOI 1609
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And: Errata: SPMag(34), No. 1, January 2017, pp. 93-93.
IEEE DOI 1702
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Choi, Y., Han, S.I., Kong, S.H., Ko, H.,
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Accidents BibRef

Perrett, T., Mirmehdi, M., Dias, E.,
Visual Monitoring of Driver and Passenger Control Panel Interactions,
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IEEE DOI 1702
Cameras BibRef

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Brain modeling BibRef

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Li, G., Chung, W.Y.,
Combined EEG-Gyroscope-tDCS Brain Machine Interface System for Early Management of Driver Drowsiness,
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IEEE DOI 1801
Brain-Computer Interface. Biomedical monitoring, Brain-computer interfaces, Electrodes, Electroencephalography, Gyroscopes, Sensors, Vehicles, transcranial direct current stimulation (tDCS) BibRef

Zhao, L.[Lei], Wang, Z.C.[Zeng-Cai], Wang, X.J.[Xiao-Jin], Liu, Q.[Qing],
Driver drowsiness detection using facial dynamic fusion information and a DBN,
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Jeong, M., Ko, B.C., Kwak, S., Nam, J.,
Driver Facial Landmark Detection in Real Driving Situations,
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IEEE DOI 1811
Shape, Face, Cameras, Vehicles, Monitoring, Facial landmark detection, weighted random forest regressor, RANSAC, global face model, real driving situation BibRef

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Li, Z.P.[Zheng-Ping], Zhang, K.[Kai], Chen, B.K.[Bo-Kui], Dong, Y.H.[Yu-Han], Zhang, L.[Lin],
Driver identification in intelligent vehicle systems using machine learning algorithms,
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Mårtensson, H., Keelan, O., Ahlström, C.,
Driver Sleepiness Classification Based on Physiological Data and Driving Performance From Real Road Driving,
ITS(20), No. 2, February 2019, pp. 421-430.
IEEE DOI 1902
Sleep, Feature extraction, Vehicles, Electroencephalography, Electrocardiography, Roads, Electrooculography, Driver sleepiness, real driving BibRef

Silveira, C.S.[Cláudia Sofia], Cardoso, J.S.[Jaime S.], Lourenço, A.L.[André L.], Ahlström, C.[Christer],
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Deep actionlet proposals for driver's behavior monitoring,
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IEEE DOI 1902
behavioural sciences computing, cameras, driver information systems, face recognition, feature extraction, Discrete Fourier transforms BibRef

Palazzi, A.[Andrea], Abati, D.[Davide], Calderara, S.[Simone], Solera, F., Cucchiara, R.[Rita],
Predicting the Driver's Focus of Attention: The DR(eye)VE Project,
PAMI(41), No. 7, July 2019, pp. 1720-1733.
IEEE DOI 1906
Task analysis, Vehicles, Visualization, Computational modeling, Semantics, Cameras, Predictive models, Focus of attention, gaze prediction BibRef

Alletto, S., Palazzi, A.[Andrea], Solera, F., Calderara, S.[Simone], Cucchiara, R.[Rita],
DR(eye)VE: A Dataset for Attention-Based Tasks with Applications to Autonomous and Assisted Driving,
CVVT16(54-60)
IEEE DOI 1612
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Morando, A., Victor, T., Dozza, M.,
A Reference Model for Driver Attention in Automation: Glance Behavior Changes During Lateral and Longitudinal Assistance,
ITS(20), No. 8, August 2019, pp. 2999-3009.
IEEE DOI 1908
Measurement, Automation, Visualization, Roads, Automobiles, Manuals, ADAS, attention, eye tracker, glance distribution, visual behavior BibRef

Tivesten, E.[Emma], Victor, T.W.[Trent W.], Gustavsson, P.[Pär], Johansson, J.[Joel], Aust, M.L.[Mikael Ljung],
Out-of-the-loop crash prediction: the automation expectation mismatch (AEM) algorithm,
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Detecting sleep in drivers during highly automated driving: the potential of physiological parameters,
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Wang, L.[Leye], Geng, X.[Xu], Ma, X.J.[Xiao-Juan], Zhang, D.[Daqing], Yang, Q.A.[Qi-Ang],
Ridesharing car detection by transfer learning,
AI(273), 2019, pp. 1-18.
Elsevier DOI 1908
Transfer learning, Co-training, Trajectory mining BibRef

Yu, J.M.[Jong-Min], Park, S.[Sangwoo], Lee, S.W.[Sang-Wook], Jeon, M.[Moongu],
Driver Drowsiness Detection Using Condition-Adaptive Representation Learning Framework,
ITS(20), No. 11, November 2019, pp. 4206-4218.
IEEE DOI 1911
Feature extraction, Visualization, Vehicle crash testing, Sensors, Adaptation models, Automobiles, Representation learning, driver drowsiness detection BibRef

Vu, T.H.[Toan H.], Dang, A.[An], Wang, J.C.[Jia-Ching],
A Deep Neural Network for Real-Time Driver Drowsiness Detection,
IEICE(E102-D), No. 12, December 2019, pp. 2637-2641.
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Driver Monitoring Using Sparse Representation With Part-Based Temporal Face Descriptors,
ITS(21), No. 1, January 2020, pp. 346-361.
IEEE DOI 2001
Vehicles, Face, Monitoring, Mouth, Accidents, Computational modeling, Advanced driver assistance systems, driver monitoring systems, temporal face descriptors BibRef

Borghi, G.[Guido], Fabbri, M., Vezzani, R.[Roberto], Cucchiara, R.[Rita], Cucchiara, R.,
Face-from-Depth for Head Pose Estimation on Depth Images,
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IEEE DOI 2002
Pose estimation, Face, Magnetic heads, Task analysis, Lighting, Head pose estimation, CNNs BibRef

Borghi, G.[Guido], Venturelli, M.[Marco], Vezzani, R.[Roberto], Cucchiara, R.[Rita],
POSEidon: Face-from-Depth for Driver Pose Estimation,
CVPR17(5494-5503)
IEEE DOI 1711
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Deep Head Pose Estimation from Depth Data for In-Car Automotive Applications,
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Springer DOI 1806
Face, Neural networks, Pose estimation, Vehicles. BibRef

Frigieri, E.[Elia], Borghi, G.[Guido], Vezzani, R.[Roberto], Cucchiara, R.[Rita],
Fast and Accurate Facial Landmark Localization in Depth Images for In-Car Applications,
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Yang, L., Dong, K., Dmitruk, A.J., Brighton, J., Zhao, Y.,
A Dual-Cameras-Based Driver Gaze Mapping System With an Application on Non-Driving Activities Monitoring,
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IEEE DOI 2010
Vehicles, Cameras, Feature extraction, Face, Monitoring, Visualization, Gaze tracking, Driver attention evaluation, Level 3 automation, heat map BibRef

Yang, L.C.[Li-Chao], Dong, K.[Kuo], Ding, Y.[Yan], Brighton, J.[James], Zhan, Z.F.[Zhen-Fei], Zhao, Y.F.[Yi-Fan],
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PR(116), 2021, pp. 107955.
Elsevier DOI 2106
Driver behaviour, Level 3 automation, Non-driving related task, activities identification BibRef

Yin, J.L., Chen, B.H., Lai, K.H.R.,
Driver Danger-Level Monitoring System Using Multi-Sourced Big Driving Data,
ITS(21), No. 12, December 2020, pp. 5271-5282.
IEEE DOI 2012
Vehicles, Feature extraction, Biomedical monitoring, Monitoring, Roads, Analytical models, Collaboration, Danger-level analysis, multi-sourced driving data BibRef

Hu, Y., Lu, M., Xie, C., Lu, X.,
Driver Drowsiness Recognition via 3D Conditional GAN and Two-Level Attention Bi-LSTM,
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IEEE DOI 2012
Generative adversarial networks, Vehicles, Feature extraction, bidirectional long short-term memory BibRef

Yang, H., Liu, L., Min, W., Yang, X., Xiong, X.,
Driver Yawning Detection Based on Subtle Facial Action Recognition,
MultMed(23), 2021, pp. 572-583.
IEEE DOI 2102
convolutional neural nets, deep learning (artificial intelligence), 3D deep learning network BibRef

Jiang, Y., Zhang, Y., Lin, C., Wu, D., Lin, C.T.,
EEG-Based Driver Drowsiness Estimation Using an Online Multi-View and Transfer TSK Fuzzy System,
ITS(22), No. 3, March 2021, pp. 1752-1764.
IEEE DOI 2103
Brain modeling, Electroencephalography, Estimation, Vehicles, Fuzzy systems, Feature extraction, Accidents, Transfer learning, EEG BibRef

Persson, A.[Anna], Jonasson, H.[Hanna], Fredriksson, I.[Ingemar], Wiklund, U.[Urban], Ahlström, C.[Christer],
Heart Rate Variability for Classification of Alert Versus Sleep Deprived Drivers in Real Road Driving Conditions,
ITS(22), No. 6, June 2021, pp. 3316-3325.
IEEE DOI 2106
Sleep, Heart rate variability, Vehicles, Feature extraction, Measurement, Roads, Driver sleepiness, detection, classification, heart rate variability BibRef

Balam, V.P.[Venkata Phanikrishna], Sameer, V.U.[Venkata Udaya], Chinara, S.[Suchismitha],
Automated classification system for drowsiness detection using convolutional neural network and electroencephalogram,
IET-ITS(15), No. 4, 2021, pp. 514-524.
DOI Link 2106
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Lv, K.[Kai], Sheng, H.[Hao], Xiong, Z.[Zhang], Li, W.[Wei], Zheng, L.[Liang],
Improving Driver Gaze Prediction With Reinforced Attention,
MultMed(23), 2021, pp. 4198-4207.
IEEE DOI 2112
Task analysis, Computational modeling, Vehicles, Predictive models, Hidden Markov models, Semantics, deep learning BibRef

Zhou, F.[Feng], Yang, X.J.[X. Jessie], de Winter, J.C.F.[Joost C. F.],
Using Eye-Tracking Data to Predict Situation Awareness in Real Time During Takeover Transitions in Conditionally Automated Driving,
ITS(23), No. 3, March 2022, pp. 2284-2295.
IEEE DOI 2203
Particle measurements, Atmospheric measurements, Vehicles, Task analysis, Time measurement, Predictive models, explainability BibRef

Hu, T.C.[Tian-Cheng], Jha, S.[Sumit], Busso, C.[Carlos],
Temporal Head Pose Estimation From Point Cloud in Naturalistic Driving Conditions,
ITS(23), No. 7, July 2022, pp. 8063-8076.
IEEE DOI 2207
Feature extraction, Pose estimation, Magnetic heads, Vehicles, Deep learning, Cameras, Driver head pose estimation, deep learning, temporal modeling BibRef

Huang, J.L.[Jian-Ling], Long, Y.[Yan], Zhao, X.H.[Xiao-Hua],
Driver Glance Behavior Modeling Based on Semi-Supervised Clustering and Piecewise Aggregate Representation,
ITS(23), No. 7, July 2022, pp. 8396-8411.
IEEE DOI 2207
Vehicles, Mirrors, Hidden Markov models, Visualization, Task analysis, Spatiotemporal phenomena, Automobiles, two-dimensional dynamic time warping BibRef

Qian, K.[Kun], Koike, T.[Tomoya], Nakamura, T.[Toru], Schuller, B.W.[Björn W.], Yamamoto, Y.[Yoshiharu],
Learning Multimodal Representations for Drowsiness Detection,
ITS(23), No. 8, August 2022, pp. 11539-11548.
IEEE DOI 2208
Brain modeling, Vehicles, Data models, Feature extraction, Electroencephalography, Predictive models, Machine learning, deep learning BibRef

Qin, L.[Long], Shi, Y.[Yi], He, Y.H.[Ya-Hui], Zhang, J.R.[Jun-Rui], Zhang, X.S.[Xian-Shi], Li, Y.J.[Yong-Jie], Deng, T.[Tao], Yan, H.M.[Hong-Mei],
ID-YOLO: Real-Time Salient Object Detection Based on the Driver's Fixation Region,
ITS(23), No. 9, September 2022, pp. 15898-15908.
IEEE DOI 2209
Vehicles, Object detection, Videos, Predictive models, Visualization, Task analysis, Vehicle dynamics, Visual attention, eye tracking, traffic driving BibRef

Ahmed, M.[Muneeb], Masood, S.[Sarfaraz], Ahmad, M.[Musheer], El-Latif, A.A.A.[Ahmed A. Abd],
Intelligent Driver Drowsiness Detection for Traffic Safety Based on Multi CNN Deep Model and Facial Subsampling,
ITS(23), No. 10, October 2022, pp. 19743-19752.
IEEE DOI 2210
Brain modeling, Feature extraction, Computational modeling, Vehicles, Convolution, Physiology, Kernel, multitask cascaded convolutional networks (MTCNN) BibRef

Baccour, M.H.[Mohamed Hedi], Driewer, F.[Frauke], Schäck, T.[Tim], Kasneci, E.[Enkelejda],
Comparative Analysis of Vehicle-Based and Driver-Based Features for Driver Drowsiness Monitoring by Support Vector Machines,
ITS(23), No. 12, December 2022, pp. 23164-23178.
IEEE DOI 2212
Vehicles, Monitoring, Behavioral sciences, Cameras, Safety, Feature extraction, Biomedical monitoring, Drowsiness, road safety, feature selection BibRef

Mou, L.[Luntian], Zhou, C.[Chao], Xie, P.[Pengtao], Zhao, P.F.[Peng-Fei], Jain, R.[Ramesh], Gao, W.[Wen], Yin, B.C.[Bao-Cai],
Isotropic Self-Supervised Learning for Driver Drowsiness Detection With Attention-Based Multimodal Fusion,
MultMed(25), 2023, pp. 529-542.
IEEE DOI 2302
Feature extraction, Convolutional neural networks, Videos, Hidden Markov models, Vehicles, Dictionaries, multimodal fusion model BibRef

Wörle, J.[Johanna], Metz, B.[Barbara], Prill, A.[Andy],
How to Induce Drowsiness When Testing Driver Drowsiness and Attention Warning (DDAW) Systems,
ITS(24), No. 5, May 2023, pp. 4758-4764.
IEEE DOI 2305
Sleep, Vehicles, Testing, Regulation, Safety, Particle measurements, Europe, Drowsiness detection, type approval, test procedure, EU regulation BibRef

Lu, Y.S.[Yan-Sha], Liu, C.S.[Chun-Sheng], Chang, F.L.[Fa-Liang], Liu, H.[Hui], Huan, H.Q.[Heng-Qiang],
JHPFA-Net: Joint Head Pose and Facial Action Network for Driver Yawning Detection Across Arbitrary Poses in Videos,
ITS(24), No. 11, November 2023, pp. 11850-11863.
IEEE DOI 2311
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Chougule, A.[Amit], Shah, J.[Jash], Chamola, V.[Vinay], Kanhere, S.[Salil],
Enabling Safe ITS: EEG-Based Microsleep Detection in VANETs,
ITS(24), No. 12, December 2023, pp. 15773-15783.
IEEE DOI 2312
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Yang, L.[Lie], Yang, H.H.[Hao-Han], Wei, H.[Henglai], Hu, Z.X.[Zhong-Xu], Lv, C.[Chen],
Video-Based Driver Drowsiness Detection With Optimised Utilization of Key Facial Features,
ITS(25), No. 7, July 2024, pp. 6938-6950.
IEEE DOI 2407
Feature extraction, Electroencephalography, Mouth, Vehicles, Physiology, Interference, Facial features, local facial areas BibRef

Gong, P.L.[Pei-Liang], Wang, P.P.[Peng-Pai], Zhou, Y.Y.[Yue-Ying], Wen, X.[Xuyun], Zhang, D.Q.[Dao-Qiang],
TFAC-Net: A Temporal-Frequential Attentional Convolutional Network for Driver Drowsiness Recognition With Single-Channel EEG,
ITS(25), No. 7, July 2024, pp. 7004-7016.
IEEE DOI 2407
Electroencephalography, Feature extraction, Vehicles, Fatigue, Task analysis, Deep learning, Convolutional neural networks, attention mechanism BibRef

Zemblys, R.[Raimondas], Ahlström, C.[Christer], Kircher, K.[Katja], Finér, S.[Svitlana],
Practical aspects of measuring camera-based indicators of alcohol intoxication in manual and automated driving,
IET-ITS(18), No. 8, 2024, pp. 1408-1427.
DOI Link 2408
advanced driver assistance systems, automotive engineering, drugs, gaze tracking BibRef

Camberg, S.[Simone], Hüllermeier, E.[Eyke],
An Extensive Analysis of Different Approaches to Driver Gaze Classification,
ITS(25), No. 11, November 2024, pp. 16435-16448.
IEEE DOI 2411
Vehicles, Cameras, Estimation, Magnetic heads, Feature extraction, Accuracy, Task analysis, Driver monitoring systems, gaze estimation BibRef

Balam, V.P.[Venkata Phanikrishna],
Systematic Review of Single-Channel EEG-Based Drowsiness Detection Methods,
ITS(25), No. 11, November 2024, pp. 15210-15228.
IEEE DOI 2411
Electroencephalography, Feature extraction, Brain modeling, Accuracy, Solid modeling, Sleep, Monitoring, signal processing BibRef

Zhang, J.M.[Jia-Ming], Zhang, F.Z.[Fang-Zuo], Wei, H.T.[Hong-Tao],
PSSS-EEG: A Probabilistic-masking Self-Supervised Swin-transformer model for EEG-based drowsiness recognition,
PR(158), 2025, pp. 111005.
Elsevier DOI 2411
Electroencephalography (EEG), Drowsiness recognition, Data augmentation, Transformer, Self-supervised learning BibRef


Cheng, Y.H.[Yi-Hua], Zhu, Y.N.[Ya-Ning], Wang, Z.[Zongji], Hao, H.Q.[Hong-Quan], Liu, Y.W.[Yong-Wei], Cheng, S.Q.[Shi-Qing], Wang, X.[Xi], Chang, H.J.[Hyung Jin],
What Do You See in Vehicle? Comprehensive Vision Solution for In-Vehicle Gaze Estimation,
CVPR24(1556-1565)
IEEE DOI Code:
WWW Link. 2410
Visualization, Image resolution, Annotations, Intelligent vehicles, Face recognition, Estimation, Transformers BibRef

Lu, W.[Wei], Liu, W.J.[Wen-Jian],
EEG-based Drowsiness and Alertness Recognition Using Feature Fusion and Deep Residual Networks,
CVIDL23(300-304)
IEEE DOI 2403
Time-frequency analysis, Road accidents, Sleep, Computational modeling, Training data, Brain modeling, Deep Residual Networks BibRef

Urselmann, T.[Teun], Cañas, P.N.[Paola Natalia], Ortega, J.D.[Juan Diego], Nieto, M.[Marcos],
Semi-automatic Pipeline for Large-scale Dataset Annotation Task: A DMD Application,
InVehicle22(560-574).
Springer DOI 2304
Driver Monitoring Dataset. BibRef

Tüfekci, G.[Gülin], Kayabasi, A.[Alper], Akagündüz, E.[Erdem], Ulusoy, I.[Ilkay],
Detecting Driver Drowsiness as an Anomaly Using Lstm Autoencoders,
InVehicle22(549-559).
Springer DOI 2304
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Banerjee, S.[Sandipan], Joshi, A.[Ajjen], Turcot, J.[Jay], Reimer, B.[Bryan], Mishra, T.[Taniya],
Driver Glance Classification In-the-wild: Towards Generalization Across Domains and Subjects,
FG21(1-8)
IEEE DOI 2303
Training, Visualization, Costs, Face recognition, Crops, Cameras, Data models BibRef

Sharak, S.[Salem], Das, K.[Kapotaksha], Riani, K.[Kais], Abouelenien, M.[Mohamed], Burzo, M.[Mihai], Mihalcea, R.[Rada],
Contact Versus Noncontact Detection of Driver's Drowsiness,
ICPR22(967-974)
IEEE DOI 2212
Visualization, Costs, Cameras, Hardware, Planning, Reliability BibRef

Ghosh, S.[Shreya], Dhall, A.[Abhinav], Sharma, G.[Garima], Gupta, S.[Sarthak], Sebe, N.[Nicu],
Speak2Label: Using Domain Knowledge for Creating a Large Scale Driver Gaze Zone Estimation Dataset,
AVVision21(2896-2905)
IEEE DOI 2112
Pipelines, Lighting, Estimation, Convolutional neural networks, Labeling BibRef

Vijay, M.[Malaika], Vinayak, N.N.[Nandagopal Netrakanti], Nunna, M.[Maanvi], Natarajan, S.[Subramanyam],
Real-Time Driver Drowsiness Detection using Facial Action Units,
ICPR21(10113-10119)
IEEE DOI 2105
Training, Scalability, Face recognition, Pipelines, Neural networks, Mouth, Muscles, Facial Action Units, Transfer Learning, XGBoost, Convolutional Neural Networks BibRef

Andriyanov, N.[Nikita],
First Step Towards Creating a Software Package for Detecting the Dangerous States During Driver Eye Monitoring,
IMTA20(314-322).
Springer DOI 2103
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Theagarajan, R., Bhanu, B., Cruz, A.,
DeepDriver: Automated System For measuring Valence and Arousal in Car Driver Videos,
ICPR18(2546-2551)
IEEE DOI 1812
convolution, driver information systems, face recognition, feature extraction, feedforward neural nets, Logic gates BibRef

Dehzangi, O., Taherisadr, M.,
Driver Distraction Detection using MEL Cepstrum Representation of Galvanic Skin Responses and Convolutional Neural Networks*,
ICPR18(1481-1486)
IEEE DOI 1812
Feature extraction, Time-frequency analysis, Vehicles, Skin, Task analysis, Cepstrum, component, BibRef

Dehzangi, O., Masilamani, S.,
Unobtrusive Driver Drowsiness Prediction Using Driving Behavior from Vehicular Sensors,
ICPR18(3598-3603)
IEEE DOI 1812
Vehicles, Feature extraction, Wheels, Sleep, Predictive models, Sensors, Correlation, Driver Drowsiness, KSS, Correlation analysis, Classification & Regression BibRef

Tang, R.[Rui], Kim, J.H.[Jung Hyup], Parker, R.[Rebecca], Jeong, Y.J.[Yoo Joo],
Indicating Severity of Vehicle Accidents Using Pupil Diameter in a Driving Simulator Environment,
DHM18(647-656).
Springer DOI 1807
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García-García, M.[Miguel], Caplier, A.[Alice], Rombaut, M.[Michele],
Sleep Deprivation Detection for Real-Time Driver Monitoring Using Deep Learning,
ICIAR18(435-442).
Springer DOI 1807
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Jie, Z., Mahmoud, M., Stafford-Fraser, Q., Robinson, P., Dias, E., Skrypchuk, L.,
Analysis of Yawning Behaviour in Spontaneous Expressions of Drowsy Drivers,
FG18(571-576)
IEEE DOI 1806
Face, Feature extraction, Histograms, Mouth, Task analysis, Vehicles, Videos, driver drowsiness, facial expression, hand touches, yawning detection BibRef

Schwarz, A., Haurilet, M., Martinez, M., Stiefelhagen, R.,
DriveAHead: A Large-Scale Driver Head Pose Dataset,
CVVT17(1165-1174)
IEEE DOI 1709
Glass, Head, Lighting, Magnetic heads, Pose estimation, Vehicles BibRef

Reddy, B., Kim, Y.H., Yun, S., Seo, C., Jang, J.,
Real-Time Driver Drowsiness Detection for Embedded System Using Model Compression of Deep Neural Networks,
ECVW17(438-445)
IEEE DOI 1709
Brain modeling, Computational modeling, Face, Machine learning, Mouth, Real-time systems, Vehicles, Deep Learning, Driver Monitoring System, Drowsiness Detection, Knowledge Distillation, Model Compression., Real-time, Deep, Neural, Network BibRef

Yuen, K., Martin, S., Trivedi, M.M.,
On looking at faces in an automobile: Issues, algorithms and evaluation on naturalistic driving dataset,
ICPR16(2777-2782)
IEEE DOI 1705
Detectors, Face detection, Head, Lighting, Pose estimation, Training, Vehicles BibRef

Rangesh, A., Trivedi, M.M.,
HandyNet: A One-stop Solution to Detect, Segment, Localize & Analyze Driver Hands,
HumanPose18(1216-12167)
IEEE DOI 1812
Vehicles, Automation, Task analysis, Training, Wheels, Cameras BibRef

Martin, S., Rangesh, A., Ohn-Bar, E.[Eshed], Trivedi, M.M.[Mohan Manubhai],
Preparatory coordination of head, eyes and hands: Experimental study at intersections,
ICPR16(2783-2788)
IEEE DOI 1705
Data models, Feature extraction, Head, Iris, Predictive models, Radio frequency, Vehicles BibRef

Le, T.H.N., Zhu, C.C.[Chen-Chen], Zheng, Y.T.[Yu-Tong], Luu, K.[Khoa], Savvides, M.,
Robust hand detection in Vehicles,
ICPR16(573-578)
IEEE DOI 1705
Convolution, Databases, Feature extraction, Neural networks, Proposals, Robustness, Vehicles BibRef

Wu, B.F.[Bing-Fei], Chu, Y.W.[Yun-Wei], Huang, P.W.[Po-Wei], Chung, M.L.[Meng-Liang], Lin, T.M.[Tzu-Min],
A Motion Robust Remote-PPG Approach to Driver's Health State Monitoring,
CVTSV16(I: 463-476).
Springer DOI 1704
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Weng, C.H.[Ching-Hua], Lai, Y.H.[Ying-Hsiu], Lai, S.H.[Shang-Hong],
Driver Drowsiness Detection via a Hierarchical Temporal Deep Belief Network,
Drowsy16(III: 117-133).
Springer DOI 1704
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Huynh, X.P.[Xuan-Phung], Park, S.M.[Sang-Min], Kim, Y.G.[Yong-Guk],
Detection of Driver Drowsiness Using 3D Deep Neural Network and Semi-Supervised Gradient Boosting Machine,
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ICIP14(214-218)
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ICPR14(1687-1691)
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Nakamura, T., Maejima, A., Morishima, S.,
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ACPR13(749-753)
IEEE DOI 1408
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Kang, H.B.[Hang-Bong],
Various Approaches for Driver and Driving Behavior Monitoring: A Review,
CVVT13(616-623)
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Florea, L.[Laura], Florea, C.[Corneliu], Vranceanu, R.[Ruxandra], Vertan, C.[Constantin],
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Craye, C.[Céline], Karray, F.[Fakhri],
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Li, X.P.[Xuan-Peng], Seignez, E., Loonis, P.,
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Zhao, S.F.[Shuan-Feng], Xu, G.H.[Guang-Hua], Tao, T.F.[Tang-Fei],
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Liao, W.H.[Wen-Hui], Zhang, W.H.[Wei-Hong], Zhu, Z.W.[Zhi-Wei], Ji, Q.A.[Qi-Ang],
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Batista, J.P.[Jorge P.],
A Real-Time Driver Visual Attention Monitoring System,
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Krumm, J., Kirk, G.,
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Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Driver Distraction Analysis, Driver Attention, Driver Inattention .


Last update:Nov 26, 2024 at 16:40:19