16.7.2.8.3 Driver Distraction Analysis, Driver Attention, Driver Inattention

Yüce, A., Gao, H., Cuendet, G.L., Thiran, J.P.,
Action Units and Their Cross-Correlations for Prediction of Cognitive Load during Driving,
AffCom(8), No. 2, April 2017, pp. 161-175.
IEEE DOI 1706
Accidents, Databases, Feature extraction, Gold, Monitoring, Vehicles, Visualization, Affect sensing and analysis, affective computing applications, driver cognitive distraction, emotional corpora, facial expression, vehicle, operation BibRef

Muñoz-Organero, M., Corcoba-Magaña, V.,
Predicting Upcoming Values of Stress While Driving,
ITS(18), No. 7, July 2017, pp. 1802-1811.
IEEE DOI 1706
Heart rate variability, Physiology, Sensors, Skin, Stress, Vehicles, Stress level prediction, machine learning, stress level classification, stress-friendly, driving, behavior BibRef

Lee, B.G., Chung, W.Y.,
Wearable Glove-Type Driver Stress Detection Using a Motion Sensor,
ITS(18), No. 7, July 2017, pp. 1835-1844.
IEEE DOI 1706
Accelerometers, Biomedical monitoring, Mobile handsets, Stress, Stress measurement, Vehicles, Wheels, Driver assistance, healthcare sensor, inertial motion unit, stress monitoring, wearable, system BibRef

Tran, D.[Duy], Do, H.M.[Ha Manh], Sheng, W.H.[Wei-Hua], Bai, H.[He], Chowdhary, G.[Girish],
Real-time detection of distracted driving based on deep learning,
IET-ITS(12), No. 10, December 2018, pp. 1210-1219.
DOI Link 1812
BibRef

Ben Ahmed, K., Goel, B., Bharti, P., Chellappan, S., Bouhorma, M.,
Leveraging Smartphone Sensors to Detect Distracted Driving Activities,
ITS(20), No. 9, September 2019, pp. 3303-3312.
IEEE DOI 1909
Sensors, Accelerometers, Gyroscopes, Acceleration, Automobiles, Wheels, Smart sensing, intelligent transportation systems, smartphones BibRef

Rastgoo, M.N.[Mohammad Naim], Nakisa, B.[Bahareh], Rakotonirainy, A.[Andry], Chandran, V.[Vinod], Tjondronegoro, D.[Dian],
A Critical Review of Proactive Detection of Driver Stress Levels Based on Multimodal Measurements,
Surveys(51), No. 5, January 2019, pp. Article No 88.
DOI Link 1902
Survey, Driver Stress. BibRef

Aksjonov, A., Nedoma, P., Vodovozov, V., Petlenkov, E., Herrmann, M.,
Detection and Evaluation of Driver Distraction Using Machine Learning and Fuzzy Logic,
ITS(20), No. 6, June 2019, pp. 2048-2059.
IEEE DOI 1906
Vehicles, Task analysis, Support vector machines, Machine learning, Artificial neural networks, Machine learning algorithms, vehicle safety BibRef

Alotaibi, M.[Munif], Alotaibi, B.[Bandar],
Distracted driver classification using deep learning,
SIViP(14), No. 3, April 2020, pp. 617-624.
Springer DOI 2004
BibRef

Jegham, I.[Imen], Ben Khalifa, A.[Anouar], Alouani, I.[Ihsen], Mahjoub, M.A.[Mohamed Ali],
A novel public dataset for multimodal multiview and multispectral driver distraction analysis: 3MDAD,
SP:IC(88), 2020, pp. 115960.
Elsevier DOI 2009
Safe driving, Intelligent transportation system, Driver distraction, Multiview, Multimodal, Multispectral, Public dataset BibRef

Masood, S.[Sarfaraz], Rai, A.[Abhinav], Aggarwal, A.[Aakash], Doja, M.N., Ahmad, M.[Musheer],
Detecting distraction of drivers using Convolutional Neural Network,
PRL(139), 2020, pp. 79-85.
Elsevier DOI 2011
Distracted driver, Deep learning, Convolutional Neural Network, VGG16, VGG19 BibRef

Pavlidis, I.[Ioannis], Khatri, A.[Ashik], Buddharaju, P.[Pradeep], Manser, M.[Michael], Wunderlich, R.[Robert], Akleman, E.[Ergun], Tsiamyrtzis, P.[Panagiotis],
Biofeedback Arrests Sympathetic and Behavioral Effects in Distracted Driving,
AffCom(12), No. 2, April 2021, pp. 453-465.
IEEE DOI 2106
Biological control systems, Vehicles, Drives, Image color analysis, Imaging, Visualization, Biomedical monitoring, Biofeedback, cusum BibRef

Chen, J.[Jie], Jiang, Y.N.[Ya-Nan], Huang, Z.X.[Zhi-Xiang], Guo, X.H.[Xiao-Hui], Wu, B.C.[Bo-Cai], Sun, L.[Long], Wu, T.[Tao],
Fine-Grained Detection of Driver Distraction Based on Neural Architecture Search,
ITS(22), No. 9, September 2021, pp. 5783-5801.
IEEE DOI 2109
Vehicles, Accidents, Manuals, Roads, Feature extraction, Safety, Neural architecture search, intelligent transportation systems BibRef

Jin, L.S.[Li-Sheng], Hua, Q.[Qiang], Zhang, S.R.[Shun-Ran], Guo, B.C.[Bai-Cang],
Stacking-based ensemble learning method for cognitive distraction state recognition for drivers in traditional and connected environments,
IET-ITS(16), No. 1, 2022, pp. 114-132.
DOI Link 2112
cognitive distraction, connected environment, intelligent vehicle, stacking-based ensemble learning method BibRef

Zhang, Y.L.[Yu-Le], Zhu, S.L.[Shou-Lin],
The influence of landscape intervention used as an alertness maintaining 'tool' on driving behaviour,
IET-ITS(16), No. 3, 2022, pp. 394-407.
DOI Link 2202
BibRef

Leicht, L.[Lennart], Walter, M.[Marian], Mathissen, M.[Marcel], Antink, C.H.[Christoph Hoog], Teichmann, D.[Daniel], Leonhardt, S.[Steffen],
Unobtrusive Measurement of Physiological Features Under Simulated and Real Driving Conditions,
ITS(23), No. 5, May 2022, pp. 4767-4777.
IEEE DOI 2205
Vehicles, Sensors, Temperature measurement, Heart rate, Imaging, Physiology, Webcams, Hybrid imaging, unobtrusive, vital signs, capacitive ECG BibRef

Ahlström, C.[Christer], Georgoulas, G.[George], Kircher, K.[Katja],
Towards a Context-Dependent Multi-Buffer Driver Distraction Detection Algorithm,
ITS(23), No. 5, May 2022, pp. 4778-4790.
IEEE DOI 2205
Vehicles, Roads, Mirrors, Monitoring, Gaze tracking, Visualization, AttenD, classification, detection, inattention BibRef

Bakker, B.[Bram], Zablocki, B.[Bartosz], Baker, A.[Angela], Riethmeister, V.[Vanessa], Marx, B.[Bernd], Iyer, G.[Girish], Anund, A.[Anna], Ahlström, C.[Christer],
A Multi-Stage, Multi-Feature Machine Learning Approach to Detect Driver Sleepiness in Naturalistic Road Driving Conditions,
ITS(23), No. 5, May 2022, pp. 4791-4800.
IEEE DOI 2205
Sleep, Vehicles, Fatigue, Feature extraction, Roads, Hidden Markov models, Faces, Fatigue detection, video-based, field trial BibRef

Lu, K.[Ke], Karlsson, J.[Johan], Dahlman, A.S.[Anna Sjörs], Sjöqvist, B.A.[Bengt Arne], Candefjord, S.[Stefan],
Detecting Driver Sleepiness Using Consumer Wearable Devices in Manual and Partial Automated Real-Road Driving,
ITS(23), No. 5, May 2022, pp. 4801-4810.
IEEE DOI 2205
Sleep, Vehicles, Heart rate variability, Monitoring, Biomedical monitoring, Automation, Particle measurements, machine learning BibRef

Perello-March, J.R.[Jaume R.], Burns, C.G.[Christopher G.], Birrell, S.A.[Stewart A.], Woodman, R.[Roger], Elliott, M.T.[Mark T.],
Physiological Measures of Risk Perception in Highly Automated Driving,
ITS(23), No. 5, May 2022, pp. 4811-4822.
IEEE DOI 2205
Vehicles, Monitoring, Task analysis, Biomedical monitoring, Skin, Stress, Human factors, Driver state monitoring, risk perception BibRef

Mathissen, M.[Marcel], Hennes, N.[Nikica], Faller, F.[Fabian], Leonhardt, S.[Steffen], Teichmann, D.[Daniel],
Investigation of Three Potential Stress Inducement Tasks During On-Road Driving,
ITS(23), No. 5, May 2022, pp. 4823-4832.
IEEE DOI 2205
Stress, Task analysis, Vehicles, Physiology, Heart rate variability, Protocols, Automation, Stress, workload, driver, sensor, ecg, hrv BibRef

Hwang, S.[Steven], Banerjee, A.G.[Ashis G.], Boyle, L.N.[Linda Ng],
Predicting Driver's Transition Time to a Secondary Task Given an in-Vehicle Alert,
ITS(23), No. 5, May 2022, pp. 4739-4745.
IEEE DOI 2205
Vehicles, Hidden Markov models, Task analysis, Data models, Predictive models, Time factors, Information processing, prediction BibRef

Pipkorn, L.[Linda], Victor, T.[Trent], Dozza, M.[Marco], Tivesten, E.[Emma],
Automation Aftereffects: The Influence of Automation Duration, Test Track and Timings,
ITS(23), No. 5, May 2022, pp. 4746-4757.
IEEE DOI 2205
Automation, Vehicles, Manuals, Human factors, Task analysis, TV, Wheels, Automated driving, driver response, driving performance, automation BibRef

Bohrmann, D.[Dominique], Bruder, A.[Anna], Bengler, K.[Klaus],
Effects of Dynamic Visual Stimuli on the Development of Carsickness in Real Driving,
ITS(23), No. 5, May 2022, pp. 4833-4842.
IEEE DOI 2205
Light emitting diodes, Visualization, Vehicle dynamics, Dynamics, Color, Automobiles, Task analysis, Autonomous vehicles, carsickness, visual feedback system BibRef

Fang, J.W.[Jian-Wu], Yan, D.X.[Ding-Xin], Qiao, J.H.[Jia-Huan], Xue, J.R.[Jian-Ru], Yu, H.K.[Hong-Kai],
DADA: Driver Attention Prediction in Driving Accident Scenarios,
ITS(23), No. 6, June 2022, pp. 4959-4971.
IEEE DOI 2206
Vehicles, Semantics, Accidents, Visualization, Roads, Convolution, Predictive models, Driver attention prediction, driving accident scenarios BibRef

Xu, J.W.[Jia-Wei], Park, S.H.[Seop Hyeong], Zhang, X.Q.[Xiao-Qin], Hu, J.[Jie],
The Improvement of Road Driving Safety Guided by Visual Inattentional Blindness,
ITS(23), No. 6, June 2022, pp. 4972-4981.
IEEE DOI 2206
Visualization, Task analysis, Safety, Blindness, Vehicles, Human factors, Computational modeling, Road driving safety, eye fixation BibRef

Amadori, P.V.[Pierluigi Vito], Fischer, T.[Tobias], Demiris, Y.F.[Yi-Fannis],
HammerDrive: A Task-Aware Driving Visual Attention Model,
ITS(23), No. 6, June 2022, pp. 5573-5585.
IEEE DOI 2206
Visualization, Vehicles, Task analysis, Predictive models, Computational modeling, Real-time systems, HAMMER BibRef

Qin, B.B.[Bin-Bin], Qian, J.B.[Jiang-Bo], Xin, Y.[Yu], Liu, B.S.[Bai-Song], Dong, Y.H.[Yi-Hong],
Distracted Driver Detection Based on a CNN With Decreasing Filter Size,
ITS(23), No. 7, July 2022, pp. 6922-6933.
IEEE DOI 2207
Convolution, Feature extraction, Real-time systems, Vehicles, Graphics processing units, Deep learning, Task analysis, CNN BibRef

Li, P.H.[Peng-Hua], Yang, Y.F.[Yi-Feng], Grosu, R.[Radu], Wang, G.D.[Guo-Dong], Li, R.[Rui], Wu, Y.H.[Yue-Hong], Huang, Z.[Zeng],
Driver Distraction Detection Using Octave-Like Convolutional Neural Network,
ITS(23), No. 7, July 2022, pp. 8823-8833.
IEEE DOI 2207
Vehicles, Videos, Convolution, Cameras, Roads, Databases, Data collection, Naturalistic driving, octave-like convolution, lightweight neural network BibRef

Tarabay, R.[Rana], Abou-Zeid, M.[Maya],
A Dynamic Hybrid Choice Model to Quantify Stress in a Simulated Driving Environment,
ITS(23), No. 7, July 2022, pp. 6390-6405.
IEEE DOI 2207
Stress, Vehicles, Mathematical model, Task analysis, Stress measurement, Context modeling, Roads, Driver stress, state detection BibRef

Lin, C.T.[Chin-Teng], Tian, Y.Q.[Yan-Qiu], Wang, Y.K.[Yu-Kai], Do, T.T.N.[Tien-Thong Nguyen], Chang, Y.L.[Yao-Lung], King, J.T.[Jung-Tai], Huang, K.C.[Kuan-Chih], Liao, L.D.[Lun-De],
Effects of Multisensory Distractor Interference on Attentional Driving,
ITS(23), No. 8, August 2022, pp. 10395-10403.
IEEE DOI 2208
Task analysis, Electroencephalography, Visualization, Interference, Wheels, Automobiles, Australia, Attentional driving, brain oscillation BibRef

Echanobe, J.[Javier], Basterretxea, K.[Koldo], del Campo, I.[Inés], Martínez, V.[Victoria], Vidal, N.[Naiara],
Multi-Objective Genetic Algorithm for Optimizing an ELM-Based Driver Distraction Detection System,
ITS(23), No. 8, August 2022, pp. 11946-11959.
IEEE DOI 2208
Vehicles, Task analysis, Visualization, Proposals, Feature extraction, Automobiles, Genetic algorithms, DAS, feature selection BibRef

Jha, S.[Sumit], Marzban, M.F.[Mohamed F.], Hu, T.[Tiancheng], Mahmoud, M.H.[Mohamed H.], Al-Dhahir, N.[Naofal], Busso, C.[Carlos],
The Multimodal Driver Monitoring Database: A Naturalistic Corpus to Study Driver Attention,
ITS(23), No. 8, August 2022, pp. 10736-10752.
IEEE DOI 2208
Vehicles, Magnetic heads, Cameras, Head, Monitoring, Annotations, Safety, In-vehicle safety, driver visual attention, driver monitoring dataset BibRef

Li, P.H.[Peng-Hui], Li, Y.B.[Yi-Bing], Yao, Y.[Yao], Wu, C.X.[Chang-Xu], Nie, B.B.[Bing-Bing], Li, S.E.[Shengbo Eben],
Sensitivity of Electrodermal Activity Features for Driver Arousal Measurement in Cognitive Load: The Application in Automated Driving Systems,
ITS(23), No. 9, September 2022, pp. 14954-14967.
IEEE DOI 2209
Vehicles, Skin, Physiology, Sensitivity, Safety, Task analysis, Heart rate, Automated driving systems, driver arousal, skin conductance response (SCR) BibRef

Xu, J.W.[Jia-Wei], Zhang, X.Q.[Xiao-Qin], Park, S.H.[Seop Hyeong], Guo, K.[Kun],
The Alleviation of Perceptual Blindness During Driving in Urban Areas Guided by Saccades Recommendation,
ITS(23), No. 9, September 2022, pp. 16386-16396.
IEEE DOI 2209
Visualization, Vehicles, Task analysis, Blindness, Feature extraction, Delays, Roads, Saccades recommendation, human factors in driving BibRef

Zuo, X.[Xin], Zhang, C.[Chi], Cong, F.[Fengyu], Zhao, J.[Jian], Hämäläinen, T.[Timo],
Driver Distraction Detection Using Bidirectional Long Short-Term Network Based on Multiscale Entropy of EEG,
ITS(23), No. 10, October 2022, pp. 19309-19322.
IEEE DOI 2210
Vehicles, Electroencephalography, Feature extraction, Task analysis, Entropy, Fatigue, Complexity theory, BiLSTM BibRef

Huang, T.[Tao], Fu, R.[Rui],
Driver Distraction Detection Based on the True Driver's Focus of Attention,
ITS(23), No. 10, October 2022, pp. 19374-19386.
IEEE DOI 2210
Vehicles, Feature extraction, Convolution, Visualization, Residual neural networks, Driver distraction detection, neural network BibRef

Li, B.[Bing], Chen, J.[Jie], Huang, Z.X.[Zhi-Xiang], Wang, H.T.[Hai-Tao], Lv, J.M.[Jian-Ming], Xi, J.M.[Jing-Min], Zhang, J.[Jun], Wu, Z.C.[Zhong-Cheng],
A New Unsupervised Deep Learning Algorithm for Fine-Grained Detection of Driver Distraction,
ITS(23), No. 10, October 2022, pp. 19272-19284.
IEEE DOI 2210
Vehicles, Accidents, Feature extraction, Deep learning, Data models, Convolutional neural networks, Computational modeling, multilayer perceptron BibRef

Li, W.J.[Wen-Jing], Wang, J.[Jing], Ren, T.T.[Ting-Ting], Li, F.[Fang], Zhang, J.[Jun], Wu, Z.C.[Zhong-Cheng],
Learning Accurate, Speedy, Lightweight CNNs via Instance-Specific Multi-Teacher Knowledge Distillation for Distracted Driver Posture Identification,
ITS(23), No. 10, October 2022, pp. 17922-17935.
IEEE DOI 2210
Vehicles, Computational modeling, Brain modeling, Real-time systems, Accidents, Biomedical monitoring, Wheels, lightweight BibRef

Luo, L.X.[Long-Xi], Wu, J.P.[Jian-Ping], Fei, W.J.[Wei-Jie], Bi, L.Z.[Lu-Zheng], Fan, X.[Xinan],
Detecting Driver Cognition Alertness State From Visual Activities in Normal and Emergency Scenarios,
ITS(23), No. 10, October 2022, pp. 19497-19510.
IEEE DOI 2210
Vehicles, Cognition, Computational modeling, Brain modeling, Visualization, Iris, Faces, Driver cognition alertness state, driver visual activity BibRef

Yusof, N.M.[Nidzamuddin Md.], Karjanto, J.[Juffrizal], Hassan, M.Z.[Muhammad Zahir], Terken, J.[Jacques], Delbressine, F.[Frank], Rauterberg, M.[Matthias],
Reading During Fully Automated Driving: A Study of the Effect of Peripheral Visual and Haptic Information on Situation Awareness and Mental Workload,
ITS(23), No. 10, October 2022, pp. 19136-19144.
IEEE DOI 2210
Visualization, Task analysis, Haptic interfaces, Information systems, Vehicles, Automobiles, Situation awareness, user experience BibRef

Gan, S.[Shun], Pei, X.[Xizhe], Ge, Y.L.[Yu-Long], Wang, Q.[Qingfan], Shang, S.[Shi], Li, S.E.[Shengbo Eben], Nie, B.B.[Bing-Bing],
Multisource Adaption for Driver Attention Prediction in Arbitrary Driving Scenes,
ITS(23), No. 11, November 2022, pp. 20912-20925.
IEEE DOI 2212
Vehicles, Adaptation models, Task analysis, Visualization, Feature extraction, Computational modeling, Semantics, attention mechanism BibRef

Wang, M.[Mei], Ma, C.[Chen], Li, Z.L.[Zhan-Li], Zhang, S.M.[Si-Ming], Li, Y.C.[Yuan-Cheng],
Alertness Estimation Using Connection Parameters of the Brain Network,
ITS(23), No. 12, December 2022, pp. 25448-25457.
IEEE DOI 2212
Electroencephalography, Estimation, Scalp, Visualization, Brain modeling, Electrodes, Autonomous robots, electroencephalograph signals BibRef

Hu, Z.X.[Zhong-Xu], Zhang, Y.[Yiran], Li, Q.H.[Qing-Hua], Lv, C.[Chen],
A Novel Heterogeneous Network for Modeling Driver Attention With Multi-Level Visual Content,
ITS(23), No. 12, December 2022, pp. 24343-24354.
IEEE DOI 2212
Feature extraction, Semantics, Visualization, Estimation, Task analysis, Optical imaging, Object detection, graph neural network BibRef

Liu, D.[Dichao], Yamasaki, T.[Toshihiko], Wang, Y.[Yu], Mase, K.[Kenji], Kato, J.[Jien],
Toward Extremely Lightweight Distracted Driver Recognition With Distillation-Based Neural Architecture Search and Knowledge Transfer,
ITS(24), No. 1, January 2023, pp. 764-777.
IEEE DOI 2301
Task analysis, Vehicles, Lighting, Knowledge engineering, Training, Behavioral sciences, Distracted driving, decreasing filter size, action recognition BibRef

Balaji, A.[Aswin], Tripathi, U.[Utkarsh], Chamola, V.[Vinay], Benslimane, A.[Abderrahim], Guizani, M.[Mohsen],
Toward Safer Vehicular Transit: Implementing Deep Learning on Single Channel EEG Systems for Microsleep Detection,
ITS(24), No. 1, January 2023, pp. 1052-1061.
IEEE DOI 2301
Electroencephalography, Sleep, Brain modeling, Training, Vehicles, Internet of Things, Headphones, Brain-computer interface, accident avoidance BibRef

Wang, H.T.[Hai-Tao], Chen, J.[Jie], Huang, Z.X.[Zhi-Xiang], Li, B.[Bing], Lv, J.M.[Jian-Ming], Xi, J.[Jingmin], Wu, B.[Bocai], Zhang, J.[Jun], Wu, Z.[Zhongcheng],
FPT: Fine-Grained Detection of Driver Distraction Based on the Feature Pyramid Vision Transformer,
ITS(24), No. 2, February 2023, pp. 1594-1608.
IEEE DOI 2302
Transformers, Vehicles, Feature extraction, Convolutional neural networks, Accidents, Roads, Convolution, driving safety BibRef

Sun, Q.[Qinyu], Guo, Y.[Yingshi], Liu, Y.T.[Yong-Tao], Wang, C.[Chang], Gu, M.[Menglu], Su, Y.Q.[Yan-Qi],
Comparing the Effects of Visual Distraction in a High-Fidelity Driving Simulator and on a Real Highway,
ITS(24), No. 4, April 2023, pp. 3738-3747.
IEEE DOI 2304
Task analysis, Visualization, Vehicles, Wheels, Mirrors, Standards, Vehicle dynamics, Driving simulator, lane-keeping, validation, visual distraction BibRef

Sultana, R.[Rebeka], Ohashi, G.[Gosuke],
Prediction of Driver's Visual Attention in Critical Moment Using Optical Flow,
IEICE(E106-D), No. 5, May 2023, pp. 1018-1026.
WWW Link. 2305
BibRef

Rafi, H.[Houda], Benezeth, Y.[Yannick], Reynaud, P.[Philippe], Arnoux, E.[Emmanuel], Song, F.Y.[Fan Yang], Demonceaux, C.[Cedric],
Personalization of AI Models Based on Federated Learning for Driver Stress Monitoring,
InVehicle22(575-585).
Springer DOI 2304
BibRef

Baee, S.[Sonia], Pakdamanian, E.[Erfan], Kim, I.[Inki], Feng, L.[Lu], Ordonez, V.[Vicente], Barnes, L.[Laura],
MEDIRL: Predicting the Visual Attention of Drivers via Maximum Entropy Deep Inverse Reinforcement Learning,
ICCV21(13158-13168)
IEEE DOI 2203
Visualization, Computational modeling, Reinforcement learning, Predictive models, Benchmark testing, Entropy, Vision for robotics and autonomous vehicles BibRef

Gopinath, D.[Deepak], Rosman, G.[Guy], Stent, S.[Simon], Terahata, K.[Katsuya], Fletcher, L.[Luke], Argall, B.[Brenna], Leonard, J.[John],
MAAD: A Model and Dataset for 'Attended Awareness' in Driving,
EPIC21(3419-3429)
IEEE DOI 2112
Visualization, Computational modeling, Noise reduction, Data models, Safety BibRef

Wu, M.Y.[Ming-Yan], Zhang, X.[Xi], Shen, L.L.[Lin-Lin], Yu, H.[Hang],
Pose-aware Multi-feature Fusion Network for Driver Distraction Recognition,
ICPR21(1228-1235)
IEEE DOI 2105
Pose estimation, Feature extraction, Data mining, Accidents BibRef

Xia, Y.[Ye], Zhang, D.Q.[Dan-Qing], Kim, J.K.[Jin-Kyu], Nakayama, K.[Ken], Zipser, K.[Karl], Whitney, D.[David],
Predicting Driver Attention in Critical Situations,
ACCV18(V:658-674).
Springer DOI 1906
BibRef

Baheti, B., Gajre, S., Talbar, S.,
Detection of Distracted Driver Using Convolutional Neural Network,
AutoDrive18(1145-11456)
IEEE DOI 1812
Vehicles, Vehicle crash testing, Convolutional neural networks, Task analysis, Wheels, Roads BibRef

Borghi, G., Frigieri, E., Vezzani, R., Cucchiara, R.,
Hands on the wheel: A Dataset for Driver Hand Detection and Tracking,
FG18(564-570)
IEEE DOI 1806
Automobiles, Automotive engineering, Cameras, Task analysis, Tracking, Wheels, Hand detection, automotive, dataset BibRef

Theagarajan, R., Bhanu, B., Cruz, A., Le, B., Tambo, A.,
Novel representation for driver emotion recognition in motor vehicle videos,
ICIP17(810-814)
IEEE DOI 1803
Correlation, Emotion recognition, Face, Gabor filters, Spatiotemporal phenomena, Vehicle dynamics, Videos, feature extraction BibRef

Le, T.H.N., Quach, K.G., Zhu, C., Duong, C.N., Luu, K., Savvides, M.,
Robust Hand Detection and Classification in Vehicles and in the Wild,
CVVT17(1203-1210)
IEEE DOI 1709
Databases, Feature extraction, Object detection, Proposals, Robustness, Support vector machines, Vehicles BibRef

Ou, C.J.[Chao-Jie], Ouali, C.[Chahid], Karray, F.[Fakhri],
Transfer Learning Based Strategy for Improving Driver Distraction Recognition,
ICIAR18(443-452).
Springer DOI 1807
BibRef

Koesdwiady, A.[Arief], Bedawi, S.M.[Safaa M.], Ou, C.J.[Chao-Jie], Karray, F.[Fakhri],
End-to-End Deep Learning for Driver Distraction Recognition,
ICIAR17(11-18).
Springer DOI 1706
BibRef

Ragab, A.[Amira], Craye, C.[Celine], Kamel, M.S.[Mohamed S.], Karray, F.[Fakhri],
A Visual-Based Driver Distraction Recognition and Detection Using Random Forest,
ICIAR14(I: 256-265).
Springer DOI 1410
BibRef

Rezaei, M.[Mahdi], Klette, R.[Reinhard],
Look at the Driver, Look at the Road: No Distraction! No Accident!,
CVPR14(129-136)
IEEE DOI 1409
2D to 3D modelling BibRef

Rezaei, M.[Mahdi], Klette, R.[Reinhard],
Novel Adaptive Eye Detection and Tracking for Challenging Lighting Conditions,
DTCE12(II:427-440).
Springer DOI 1304
BibRef
Earlier:
3D Cascade of Classifiers for Open and Closed Eye Detection in Driver Distraction Monitoring,
CAIP11(II: 171-179).
Springer DOI 1109
BibRef

Kutila, M.[Matti], Jokela, M.[Maria], Markkula, G.[Gustav], Rue, M.R.[Maria Romera],
Driver Distraction Detection with a Camera Vision System,
ICIP07(VI: 201-204).
IEEE DOI 0709
BibRef

Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
License Plate Recognition, Extraction, Analysis .

Last update:May 22, 2023 at 22:32:27