16.7.2.8 Surveillance of Vehicles and Occupants, Driver Monitoring

Huang, T.[Timothy], Russell, S.[Stuart],
Object identification: A Bayesian analysis with application to traffic surveillance,
AI(103), No. 1-2, August 1998, pp. 77-93.
Elsevier DOI The task of deciding that two objects are really the same object. Define an identity criterion and an appearance probability. Recognize cars in widely spaced cameras. BibRef 9808

Koller, D.[Dieter], Weber, J.W.[Joseph W.], Huang, T.S., Malik, J., Ogasawara, G., Rao, B., Russell, S.,
Towards Robust Automatic Traffic Scene Analysis in Real-Time,
ICPR94(A:126-131).
IEEE DOI BibRef 9400

Aste, M., Rossi, M., Cattoni, R., Caprile, B.,
Visual Routines for Real Time Monitoring of Vehicle Behavior,
MVA(11), No. 1, 1998, pp. 16-23.
Springer DOI 9808
BibRef

Burlina, P., Chellappa, R.,
Temporal Analysis of Motion in Video Sequences Through Predictive Operators,
IJCV(28), No. 2, June-July 1998, pp. 175-192.
DOI Link 9808
BibRef

Burlina, P., Chellappa, R., Lin, C.L.,
A Spectral Attentional Mechanism Tuned to Object Configurations,
IP(6), No. 8, August 1997, pp. 1117-1128.
IEEE DOI 9708

See also Adaptive Target Detection in Foliage-Penetrating SAR Images Using Alpha-Stable Models. BibRef

Chellappa, R., Burlina, P., Zheng, Q., Shekhar, C., Davis, L.S.,
Temporal Analysis of Vehicular Activities from SAR/EO,
DARPA97(415-424). BibRef 9700

Chellappa, R.[Rama], Burlina, P.[Phillipe], Davis, L.S.[Larry S.], Rosenfeld, A.[Azriel],
SAR/EO Vehicular Activity Analysis System Guided by Temporal and Contextual Information,
DARPA98(615-620). BibRef 9800

Burlina, P.[Philippe], Lin, B.[Bruce], Chellappa, R.[Rama],
On a Spectral Attentional Mechanism,
CVPR96(120-127).
IEEE DOI Find areas with vehicles, using spectral computations. BibRef 9600

Tunali, G.D.[Gamze D.], Chellappa, R.[Rama], Burlina, P.[Philippe],
Following and Monitoring Roads on Airborne Video,
UMD--TR3990, February 1999.
WWW Link. BibRef 9902

Cetintemel, G.D., Burlina, P.,
On-the-fly snake construction from video,
ICIP98(III: 638-642).
IEEE DOI 9810
BibRef

Burlina, P., Cetintemel, G.D.,
On-the-Fly Road Tracking from video,
DARPA98(223-227). Snakes BibRef 9800

Davis, L.S.[Larry S.], Challappa, R.[Rama], Rosenfeld, A.[Azriel], Harwood, D.[David], Haritaoglu, I.[Ismail], Cutler, R.[Ross],
Visual Surveillance and Monitoring,
DARPA98(73-76). BibRef 9800

Chellappa, R., Burlina, P., Phillips, W., Cetintemel, G.D., Shekhar, C., Parameswaran, V., Davis, L.S., and Rosenfeld, A.,
Context-based Analysis and Reasoning on Vehicular Activities in SAR-EO Imagery,
UMD-- F33615, February 1998. Tracking and understanding of vehicular activity from intermittent observations.
PS File. BibRef 9802

Pavlidis, I., Morellas, V., Papanikolopoulos, N.P.,
A vehicle occupant counting system based on near-infrared phenomenology and fuzzy neural classification,
ITS(1), No. 2, June 2000, pp. 72-85.
IEEE Abstract. 0402
BibRef

Pavlidis, I., Symosek, P., Fritz, B., Bazakos, M., Papanikolopoulos, N.P.,
Automatic detection of vehicle occupants: The Imaging Problem and its solution,
MVA(11), No. 6, 2000, pp. 313-320.
Springer DOI 0005
BibRef

Pavlidis, I., Symosek, P., Fritz, B., Papanikolopoulos, N.P.,
A Near-Infrared Fusion Scheme for Automatic Detection of Vehicle Passengers,
CVBVS99(41).
IEEE DOI BibRef 9900

Masoud, O.T., Papanikolopoulos, N.P., Kwon, E.,
The use of computer vision in monitoring weaving sections,
ITS(2), No. 1, March 2001, pp. 18-25.
IEEE Abstract. 0402
BibRef

Veeraraghavan, H., Masoud, O.T., Papanikolopoulos, N.P.,
Computer vision algorithms for intersection monitoring,
ITS(4), No. 2, June 2003, pp. 78-89.
IEEE Abstract. 0402
BibRef

Atev, S., Arumugam, H., Masoud, O.T., Janardan, R., Papanikolopoulos, N.P.,
A vision-based approach to collision prediction at traffic intersections,
ITS(6), No. 4, December 2005, pp. 416-423.
IEEE DOI 0601
BibRef

Atev, S., Miller, G., Papanikolopoulos, N.P.,
Clustering of Vehicle Trajectories,
ITS(11), No. 3, September 2010, pp. 647-657.
IEEE DOI 1003
BibRef

Ferryman, J.M.[James M.], Maybank, S.J.[Stephen J.], Worrall, A.D.[Anthony D.],
Visual Surveillance for Moving Vehicles,
IJCV(37), No. 2, June 2000, pp. 187-197.
DOI Link 0008
BibRef
Earlier: VS98(Monitoring and Surveillance of Traffic Scenes). BibRef

Morris, R.J., Hogg, D.C.,
Statistical Models of Object Interaction,
IJCV(37), No. 2, June 2000, pp. 209-215.
DOI Link 0008
BibRef
Earlier: VS98(Monitoring and Surveillance of Traffic Scenes). BibRef

Shekhar, C.[Chandra], and Chellappa, R.[Rama],
Airborne Video Registration for Activity Monitoring,
VideoRegister03(Chapter 6). BibRef 0300

Jung, Y.K.[Young-Kee], Lee, K.W.[Kyu-Won], Ho, Y.S.[Yo-Sung],
Content-based event retrieval using semantic scene interpretation for automated traffic surveillance,
ITS(2), No. 3, September 2001, pp. 151-163.
IEEE Abstract. 0402
BibRef

Manolakis, D.E.,
Comment on 'Content-Based Event Retrieval Using Semantic Scene Interpretation for Automated Traffic Surveillance',
ITS(5), No. 3, September 2004, pp. 219-219.
IEEE Abstract. 0501

See also Content-based event retrieval using semantic scene interpretation for automated traffic surveillance. BibRef

Srinivasan, D., Jin, X.[Xin], Cheu, R.L.,
Evaluation of adaptive neural network models for freeway incident detection,
ITS(5), No. 1, March 2004, pp. 1-11.
IEEE Abstract. 0501
BibRef

Tang, S., Gao, H.,
Traffic-Incident Detection-Algorithm Based on Nonparametric Regression,
ITS(6), No. 1, March 2005, pp. 38-42.
IEEE Abstract. 0501
BibRef

Oh, C.[Cheol], Ritchie, S.G.[Stephen G.],
Recognizing vehicle classification information from blade sensor signature,
PRL(28), No. 9, 1 July 2007, pp. 1041-1049.
Elsevier DOI 0704
Probabilistic neural network; Vehicle classification; Traffic surveillance BibRef

Takagi, A.[Akira], Imanishi, M.[Masayuki], Goto, T.[Tomoyuki], Sato, H.[Hironori],
Apparatus for protecting occupant in vehicle,
US_Patent7,139,410, Nov 21, 2006
WWW Link. BibRef 0611

Micheloni, C.[Christian], Snidaro, L.[Lauro], Foresti, G.L.[Gian Luca],
Exploiting Temporal Statistics for Events Analysis and Understanding,
IVC(27), No. 10, 2 September 2009, pp. 1459-1469.
Elsevier DOI 0906
BibRef
And: Add A3: Piciarelli, C.[Claudio], CIAP07(530-535).
IEEE DOI 0709
BibRef
Earlier: A3, A1, A2:
Event classification for automatic visual-based surveillance of parking lots,
ICPR04(III: 314-317).
IEEE DOI 0409
Apply to parking lots. Event analysis; Event understanding; Video surveillance; Security BibRef

Falcone, P., Ali, M., Sjoberg, J.,
Predictive Threat Assessment via Reachability Analysis and Set Invariance Theory,
ITS(12), No. 4, December 2011, pp. 1352-1361.
IEEE DOI 1112
BibRef

Huang, S.S.,
Discriminatively trained patch-based model for occupant classification,
IET-ITS(6), No. 2, 2012, pp. 132-138.
DOI Link 1206
BibRef

Chiverton, J.,
Helmet presence classification with motorcycle detection and tracking,
IET-ITS(6), No. 2, 2012, pp. 259-269.
DOI Link 1209
BibRef

Ranta, R., Decoster, Y., Orlewski, P.,
Detection of human presence in a vehicle by vibration analysis,
IET-ITS(6), No. 4, 2012, pp. 413-420.
DOI Link 1302
BibRef

Untaroiu, C.D., Adam, T.J.,
Performance-Based Classification of Occupant Posture to Reduce the Risk of Injury in a Collision,
ITS(14), No. 2, 2013, pp. 565-573.
IEEE DOI 1307
crash simulations; injury risk reduction; occupant posture; BibRef

Zheng, R.[Rencheng], Nakano, K., Okamoto, Y., Ohori, M., Hori, S., Suda, Y.,
Evaluation of Sternocleidomastoid Muscle Activity of a Passenger in Response to a Car's Lateral Acceleration While Slalom Driving,
HMS(43), No. 4, 2013, pp. 405-415.
IEEE DOI 1307
biomechanics BibRef

Li, N., Jain, J.J., Busso, C.,
Modeling of Driver Behavior in Real World Scenarios Using Multiple Noninvasive Sensors,
MultMed(15), No. 5, 2013, pp. 1213-1225.
IEEE DOI 1307
Accuracy BibRef

Levchuk, G.[Georgiy],
Detecting co-ordinated activities from persistent surveillance,
SPIE(Newsroom), June 5, 2013
DOI Link 1307
Algorithms identifying the behavior patterns of people and vehicles in wide-area motion imagery can extract intelligence from data that is too large to process manually. BibRef

Martin, S., Tawari, A., Trivedi, M.M.,
Toward Privacy-Protecting Safety Systems for Naturalistic Driving Videos,
ITS(15), No. 4, August 2014, pp. 1811-1822.
IEEE DOI 1410
behavioural sciences computing BibRef

Hwang, Y.[Yoonsook], Yoon, D.[Daesub], Kim, H.S.[Hyun Suk], Kim, K.H.[Kyong-Ho],
A Validation Study on a Subjective Driving Workload Prediction Tool,
ITS(15), No. 4, August 2014, pp. 1835-1843.
IEEE DOI 1410
automobiles BibRef

Yu, T.[Teng], Shin, H.[Hyunchul],
Detecting partially occluded vehicles with geometric and likelihood reasoning,
IET-CV(9), No. 2, 2015, pp. 174-183.
DOI Link 1506
geometry BibRef

Agostino, C., Saidi, A., Scouarnec, G., Chen, L.,
Learning-Based Driving Events Recognition and Its Application to Digital Roads,
ITS(16), No. 4, August 2015, pp. 2155-2166.
IEEE DOI 1508
Acceleration BibRef

Yan, C., Coenen, F., Zhang, B.,
Driving posture recognition by convolutional neural networks,
IET-CV(10), No. 2, 2016, pp. 103-114.
DOI Link 1603
driver information systems BibRef

Moreira-Matias, L., Farah, H.,
On Developing a Driver Identification Methodology Using In-Vehicle Data Recorders,
ITS(18), No. 9, September 2017, pp. 2387-2396.
IEEE DOI 1709
Cohen Kappa agreement score, driver identification methodology, Face, Iris recognition BibRef

Zhou, X.[Xiang], Yao, D.[Di], Zhu, M.K.[Mian-Kuan], Zhang, X.L.[Xiao-Liang], Qi, L.F.[Ling-Fei], Pan, H.Y.[Hong-Ye], Zhu, X.[Xin], Wang, Y.[Yuan], Zhang, Z.[Zutao],
Vigilance detection method for high-speed rail using wireless wearable EEG collection technology based on low-rank matrix decomposition,
IET-ITS(12), No. 8, October 2018, pp. 819-825.
DOI Link 1809
BibRef

Xu, M.L.[Ming-Liang], Fang, H.[Hao], Lv, P.[Pei], Cui, L.[Lisha], Zhang, S.[Shuo], Zhou, B.[Bing],
D-STC: Deep learning with spatio-temporal constraints for train drivers detection from videos,
PRL(119), 2019, pp. 222-228.
Elsevier DOI 1902
Deep learning, Train driver detection, Spatio-temporal constraints, Dynamic adjustment BibRef

Saruchi, S.A.[Sarah Atifah], Ariff, M.H.M.[Mohd Hatta Mohammed], Zamzuri, H.[Hairi], Hassan, N.[Nurhaffizah], Wahid, N.[Nurbaiti],
Artificial neural network for modelling of the correlation between lateral acceleration and head movement in a motion sickness study,
IET-ITS(13), No. 2, February 2019, pp. 340-346.
DOI Link 1902
BibRef

Nneji, V.C., Cummings, M.L., Stimpson, A.J.,
Predicting Locomotive Crew Performance in Rail Operations with Human and Automation Assistance,
HMS(49), No. 3, June 2019, pp. 250-258.
IEEE DOI 1906
Task analysis, Rails, Automation, Conductors, Load modeling, Interviews, Transportation, Automation, workload BibRef

Yogameena, B., Menaka, K., Perumaal, S.S.[S. Saravana],
Deep learning-based helmet wear analysis of a motorcycle rider for intelligent surveillance system,
IET-ITS(13), No. 7, July 2019, pp. 1190-1198.
DOI Link 1906
BibRef

Hu, Y.C.[Yao-Cong], Lu, M.Q.[Ming-Qi], Lu, X.B.[Xiao-Bo],
Driving behaviour recognition from still images by using multi-stream fusion CNN,
MVA(30), No. 5, July 2019, pp. 851-865.
Springer DOI 1907
BibRef

He, D., Donmez, B., Liu, C.C., Plataniotis, K.N.,
High Cognitive Load Assessment in Drivers Through Wireless Electroencephalography and the Validation of a Modified N-Back Task,
HMS(49), No. 4, August 2019, pp. 362-371.
IEEE DOI 1908
Task analysis, Electroencephalography, Vehicles, Wireless communication, Roads, Wireless sensor networks, physiological measures BibRef

Young, K.L.[Kristie L.], Osborne, R.[Rachel], Koppel, S.[Sjaan], Charlton, J.L.[Judith L.], Grzebieta, R.[Raphael], Williamson, A.[Ann], Haworth, N.[Narelle], Woolley, J.[Jeremy], Senserrick, T.[Teresa],
What contextual and demographic factors predict drivers' decision to engage in secondary tasks?,
IET-ITS(13), No. 8, August 2019, pp. 1218-1223.
DOI Link 1908
BibRef

Petzoldt, T.[Tibor], Schleinitz, K.[Katja],
To text or not to text- drivers' interpretation of traffic situations as the basis for their decision to (not) engage in text messaging,
IET-ITS(13), No. 8, August 2019, pp. 1224-1229.
DOI Link 1908
BibRef

Perttula, A.[Arto], Nguyen, N.[Nhan], Collin, J.[Jussi], Jokinen, J.P.[Jani-Pekka],
Vehicle type detection and passenger satisfaction analysis using smartphone sensors and digital surveys,
IET-ITS(13), No. 10, October 2019, pp. 1499-1506.
DOI Link 1909
BibRef

Liu, Y., Lasang, P., Pranata, S., Shen, S., Zhang, W.,
Driver Pose Estimation Using Recurrent Lightweight Network and Virtual Data Augmented Transfer Learning,
ITS(20), No. 10, October 2019, pp. 3818-3831.
IEEE DOI 1910
Pose estimation, Task analysis, Face, Computational modeling, Data models, Training, Driver joints detection, transfer learning BibRef

Jagacinski, R.J., Rizzi, E., Bloom, B.J., Turkkan, O.A., Morrison, T.N., Su, H., Wang, J.,
Drivers' Attentional Instability on a Winding Roadway,
HMS(49), No. 6, December 2019, pp. 498-507.
IEEE DOI 1912
Vehicle driving, Optimal control, Pattern formation, Biological system modeling, Tracking, Attention, driving, tracking BibRef

Yao, Z.J.[Zhi-Jie], Liu, Y.Z.[Ya-Zhou], Ji, Z.X.[Ze-Xuan], Sun, Q.S.[Quan-Sen], Lasang, P.[Pongsak], Shen, S.G.[Shen-Gmei],
3D driver pose estimation based on joint 2D-3D network,
IET-CV(14), No. 3, April 2020, pp. 84-91.
DOI Link 2003
BibRef
Earlier: ICIP19(2546-2550)
IEEE DOI 1910
Point Cloud, Infrared Image, CNNs, 3D Human Pose Estimation, Joint Network BibRef

Gonzalez-Trejo, E., Mögele, H., Pfleger, N., Hannemann, R., Strauss, D.J.,
Electroencephalographic Phase-Amplitude Coupling in Simulated Driving With Varying Modality-Specific Attentional Demand,
HMS(49), No. 6, December 2019, pp. 589-598.
IEEE DOI 1912
Task analysis, Electroencephalography, Vehicle driving, Biomarkers, Advanced driver assistance systems, Attention, driving, phase-amplitude coupling (PAC) BibRef

Abouelenien, M., Burzo, M.,
Detecting Thermal Discomfort of Drivers Using Physiological Sensors and Thermal Imaging,
IEEE_Int_Sys(34), No. 5, September 2019, pp. 3-13.
IEEE DOI 1912
Physiology, Feature extraction, Intelligent systems, Temperature sensors, Sensors BibRef

Hu, Y.C.[Yao-Cong], Lu, M.Q.[Ming-Qi], Lu, X.B.[Xiao-Bo],
Feature refinement for image-based driver action recognition via multi-scale attention convolutional neural network,
SP:IC(81), 2020, pp. 115697.
Elsevier DOI 1912
Driver action, Attention mechanism, Maximum selection unit, Fine-grained BibRef

Zheng, W., Gao, K., Li, G., Liu, W., Liu, C., Liu, J., Wang, G., Lu, B.,
Vigilance Estimation Using a Wearable EOG Device in Real Driving Environment,
ITS(21), No. 1, January 2020, pp. 170-184.
IEEE DOI 2001
Electrodes, Fabrics, Electroencephalography, Estimation, Forehead, Electrooculography, Biomedical monitoring, Vigilance estimation, real-world driving environment BibRef

Zepf, S.[Sebastian], Hernandez, J.[Javier], Schmitt, A.[Alexander], Minker, W.[Wolfgang], Picard, R.W.[Rosalind W.],
Driver Emotion Recognition for Intelligent Vehicles: A Survey,
Surveys(53), No. 3, June 2020, pp. xx-yy.
DOI Link 2007
Survey, Driver Monitoring. machine learning, emotion measurement, literature survey, Affective computing, road safety, intelligent user sensing BibRef

Pronker, A.J., Abbink, D.A., van Paassen, M.M., Mulder, M.,
Estimating an LPV Model of Driver Neuromuscular Admittance Using Grip Force as Scheduling Variable,
HMS(50), No. 5, October 2020, pp. 454-464.
IEEE DOI 2009
Admittance, Force, Linear systems, Computational modeling, Vehicles, Perturbation methods, Task analysis, Driving behavior, grip force, neuromuscular admittance BibRef

Hu, C.H., Zhang, Y., Wu, F., Lu, X.B., Liu, P., Jing, X.Y.,
Toward Driver Face Recognition in the Intelligent Traffic Monitoring Systems,
ITS(21), No. 12, December 2020, pp. 4958-4971.
IEEE DOI 2012
Lighting, Face, Face recognition, Vehicles, Deep learning, Monitoring, Facial features, Traffic driver face recognition, single sample problem BibRef

Avizzano, C.A., Tripicchio, P., Ruffaldi, E., Filippeschi, A., Jacinto-Villegas, J.M.,
Real-Time Embedded Vision System for the Watchfulness Analysis of Train Drivers,
ITS(22), No. 1, January 2021, pp. 208-218.
IEEE DOI 2012
Vehicles, Face, Cameras, Monitoring, Biomedical monitoring, Robustness, Amplitude modulation, drowsiness, driver monitoring BibRef

Hu, H.Y.[Hong-Yu], Liu, J.R.[Jia-Rui], Gao, Z.H.[Zhen-Hai], Wang, P.[Pin],
Driver identification using 1D convolutional neural networks with vehicular CAN signals,
IET-ITS(14), No. 13, 15 December 2020, pp. 1799-1809.
DOI Link 2102
BibRef

Xia, K., Gu, X., Chen, B.,
Cross-Dataset Transfer Driver Expression Recognition via Global Discriminative and Local Structure Knowledge Exploitation in Shared Projection Subspace,
ITS(22), No. 3, March 2021, pp. 1765-1776.
IEEE DOI 2103
Face recognition, Vehicles, Image recognition, Accidents, Target recognition, Training, Emotion recognition, kernel trick BibRef

Qian, P., Yuan, K., Yao, J., Fan, C., Zhang, H., Liu, Y., Lu, X.,
Residual-Network-Leveraged Vehicle-Thrown-Waste Identification in Real-Time Traffic Surveillance Videos,
ITS(22), No. 3, March 2021, pp. 1817-1826.
IEEE DOI 2103
Videos, Search problems, Real-time systems, Surveillance, Training, Manuals, Inspection, Throwing waste from vehicles (TWV), intelligent traffic BibRef

Naveed, H.[Humza], Jafri, F.[Fareed], Javed, K.[Kashif], Babri, H.A.[Haroon Atique],
Driver activity recognition by learning spatiotemporal features of pose and human object interaction,
JVCIR(77), 2021, pp. 103135.
Elsevier DOI 2106
Driver activity recognition, Feature extraction, Spatiotemporal features, Driver activity recognition dataset BibRef

Kouchak, S.M.[Shokoufeh Monjezi], Gaffar, A.[Ashraf],
Detecting Driver Behavior Using Stacked Long Short Term Memory Network With Attention Layer,
ITS(22), No. 6, June 2021, pp. 3420-3429.
IEEE DOI 2106
Automobiles, Brain modeling, Data models, Accidents, Task analysis, Safety, Artificial neural networks, attention network, vehicle safety BibRef

Pan, C.P.[Chao-Peng], Cao, H.T.[Hao-Tian], Zhang, W.W.[Wei-Wei], Song, X.L.[Xiao-Lin], Li, M.J.[Ming-Jun],
Driver activity recognition using spatial-temporal graph convolutional LSTM networks with attention mechanism,
IET-ITS(15), No. 2, 2021, pp. 297-307.
DOI Link 2106
BibRef

Du, G.L.[Guang-Long], Wang, Z.Y.[Zhi-Yao], Gao, B.[Boyu], Mumtaz, S.[Shahid], Abualnaja, K.M.[Khamael M.], Du, C.F.[Cui-Feng],
A Convolution Bidirectional Long Short-Term Memory Neural Network for Driver Emotion Recognition,
ITS(22), No. 7, July 2021, pp. 4570-4578.
IEEE DOI 2107
Heart rate, Emotion recognition, Feature extraction, Real-time systems, Facial features, Brightness, Face, CBLNN BibRef

Gu, Y.[Yuwan], Wang, Y.S.[Yu-Sheng], Shi, L.[Lin], Li, N.[Ning], Zhuang, L.H.[Li-Hua], Xu, S.[Shoukun],
Automatic detection of safety helmet wearing based on head region location,
IET-IPR(15), No. 11, 2021, pp. 2441-2453.
DOI Link 2108
BibRef

Chen, L.W.[Lien-Wu], Chen, H.M.[Hsien-Min],
Driver Behavior Monitoring and Warning With Dangerous Driving Detection Based on the Internet of Vehicles,
ITS(22), No. 11, November 2021, pp. 7232-7241.
IEEE DOI 2112
Vehicles, Monitoring, Cameras, Image sensors, Biomedical monitoring, Head, Intelligent transportation system, Internet of Vehicles, vehicle-to-vehicle communication BibRef

Jia, W.[Wei], Xu, S.[Shiquan], Liang, Z.[Zhen], Zhao, Y.[Yang], Min, H.[Hai], Li, S.[Shujie], Yu, Y.[Ye],
Real-time automatic helmet detection of motorcyclists in urban traffic using improved YOLOv5 detector,
IET-IPR(15), No. 14, 2021, pp. 3623-3637.
DOI Link 2112
BibRef

Köpüklü, O.[Okan], Hörmann, S.[Stefan], Herzog, F.[Fabian], Cevikalp, H.[Hakan], Rigoll, G.[Gerhard],
Dissected 3D CNNs: Temporal skip connections for efficient online video processing,
CVIU(215), 2022, pp. 103318.
Elsevier DOI 2201
Temporal skip connections, Efficient online video processing, 3D convolutional neural networks BibRef

Köpüklü, O.[Okan], Herzog, F.[Fabian], Rigoll, G.[Gerhard],
Comparative Analysis of CNN-based Spatiotemporal Reasoning in Videos,
HCAU20(186-202).
Springer DOI 2103
BibRef

Köpüklü, O.[Okan], Ledwon, T., Rong, Y., Kose, N., Rigoll, G.[Gerhard],
DriverMHG: A Multi-Modal Dataset for Dynamic Recognition of Driver Micro Hand Gestures and a Real-Time Recognition Framework,
FG20(77-84)
IEEE DOI 2102
Gesture recognition, Face recognition, hand gesture recognition, dataset for driver gestures, 3D CNNs BibRef

Behera, A.[Ardhendu], Wharton, Z.[Zachary], Keidel, A.[Alexander], Debnath, B.[Bappaditya],
Deep CNN, Body Pose, and Body-Object Interaction Features for Drivers' Activity Monitoring,
ITS(23), No. 3, March 2022, pp. 2874-2881.
IEEE DOI 2203
Vehicles, Feature extraction, Semantics, Computational modeling, Activity recognition, Monitoring, Image recognition, neural network-based fusion BibRef

Lu, Y.[Ying], Liu, Y.[Yufa], Shu, Y.[Yu], Yin, Y.Z.[Yue-Zhou],
Injury prediction algorithm for rear-seat occupants in advanced automatic crash notification systems,
IET-ITS(16), No. 4, 2022, pp. 474-488.
DOI Link 2203
BibRef

Perello-March, J.R.[Jaume R.], Burns, C.G.[Christopher G.], Woodman, R.[Roger], Elliott, M.T.[Mark T.], Birrell, S.A.[Stewart A.],
Driver State Monitoring: Manipulating Reliability Expectations in Simulated Automated Driving Scenarios,
ITS(23), No. 6, June 2022, pp. 5187-5197.
IEEE DOI 2206
Vehicles, Complexity theory, Biomedical monitoring, Monitoring, Task analysis, Reliability, Heart rate variability, trust in automation BibRef

Martinelli, F.[Fabio], Mercaldo, F.[Francesco], Nardone, V.[Vittoria], Santone, A.[Antonella],
Driver Identification Through Formal Methods,
ITS(23), No. 6, June 2022, pp. 5625-5637.
IEEE DOI 2206
Vehicles, Hidden Markov models, Model checking, Feature extraction, Automobiles, Brakes, Data models, Automotive, formal methods, safety BibRef

Walocha, F.[Fabian], Drewitz, U.[Uwe], Ihme, K.[Klas],
Activity and Stress Estimation Based on OpenPose and Electrocardiogram for User-Focused Level-4-Vehicles,
HMS(52), No. 4, August 2022, pp. 538-546.
IEEE DOI 2208
Stress, Rail to rail inputs, Automation, Activity recognition, Task analysis, Hidden Markov models, Biomedical monitoring, vehicle automation BibRef

Wang, J.Y.[Ji-Yang], Chai, W.H.[Wei-Heng], Venkatachalapathy, A.[Archana], Tan, K.L.[Kai Liang], Haghighat, A.[Arya], Velipasalar, S.[Senem], Adu-Gyamfi, Y.[Yaw], Sharma, A.[Anuj],
A Survey on Driver Behavior Analysis From In-Vehicle Cameras,
ITS(23), No. 8, August 2022, pp. 10186-10209.
IEEE DOI 2208
Vehicles, Task analysis, Feature extraction, Cameras, Accidents, Data mining, Driver behavior analysis, gaze, face detection, survey BibRef

Tan, M.K.[Ming-Kui], Ni, G.Q.[Geng-Qin], Liu, X.[Xu], Zhang, S.L.[Shi-Liang], Wu, X.M.[Xiang-Miao], Wang, Y.W.[Yao-Wei], Zeng, R.[Runhao],
Bidirectional Posture-Appearance Interaction Network for Driver Behavior Recognition,
ITS(23), No. 8, August 2022, pp. 13242-13254.
IEEE DOI 2208
Feature extraction, Vehicles, Task analysis, Skeleton, Optical sensors, Nickel, Deep learning, graph convolutional networks BibRef

Jiang, R.Q.[Run-Qiang], Chen, L.L.[Lan-Lan],
Driving Stress Estimation in Physiological Signals Based on Hierarchical Clustering and Multi-View Intact Space Learning,
ITS(23), No. 8, August 2022, pp. 13141-13154.
IEEE DOI 2208
Stress, Vehicles, Feature extraction, Biomedical monitoring, Physiology, Task analysis, Electrocardiography, Driving stress, physiological signals BibRef

Ding, Z.Z.[Zhe-Zhang], Xu, D.H.[Dong-Hao], Tu, C.F.[Chen-Feng], Zhao, H.J.[Hui-Jing], Moze, M.[Mathieu], Aioun, F.[François], Guillemard, F.[Franck],
Driver Identification Through Heterogeneity Modeling in Car-Following Sequences,
ITS(23), No. 10, October 2022, pp. 17143-17156.
IEEE DOI 2210
Vehicles, Data models, Automobiles, Analytical models, Feature extraction, Time series analysis, Indexes, machine learning BibRef

Chen, Z.S.[Zhong-Shan], Feng, X.N.[Xin-Ning], Zhang, S.W.[Sheng-Wei],
Emotion detection and face recognition of drivers in autonomous vehicles in IoT platform,
IVC(128), 2022, pp. 104569.
Elsevier DOI 2212
IoT, Machine learning, FR, ED BibRef

Liang, H.[Han], Seo, S.Y.[Su-Young],
UAV Low-Altitude Remote Sensing Inspection System Using a Small Target Detection Network for Helmet Wear Detection,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
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Wu, X.[Xiao], Li, Y.P.[Yu-Peng], Long, J.H.[Ji-Hui], Zhang, S.[Shun], Wan, S.[Shuai], Mei, S.H.[Shao-Hui],
A Remote-Vision-Based Safety Helmet and Harness Monitoring System Based on Attribute Knowledge Modeling,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link 2301
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Lee, S.[Sooeon], Lee, S.[Seungheyon], Kim, H.[Hyunbum],
Differential Security Barriers for Virtual Emotion Detection in Maritime Transportation Stations With Cooperative Mobile Robots and UAVs,
ITS(24), No. 2, February 2023, pp. 2461-2471.
IEEE DOI 2302
Security, Mobile robots, Transportation, Surveillance, Emotion recognition, Communication system security, UAVs BibRef

Tavakoli, A.[Arash], Boker, S.[Steven], Heydarian, A.[Arsalan],
Driver State Modeling Through Latent Variable State Space Framework in the Wild,
ITS(24), No. 2, February 2023, pp. 1879-1893.
IEEE DOI 2302
Vehicles, Human factors, Temperature measurement, Stress measurement, Task analysis, Analytical models, Psychology, transportation safety BibRef

Li, W.B.[Wen-Bo], Cui, Y.D.[Yao-Dong], Ma, Y.[Yintao], Chen, X.X.[Xing-Xin], Li, G.F.[Guo-Fa], Zeng, G.Z.[Guan-Zhong], Guo, G.[Gang], Cao, D.P.[Dong-Pu],
A Spontaneous Driver Emotion Facial Expression (DEFE) Dataset for Intelligent Vehicles: Emotions Triggered by Video-Audio Clips in Driving Scenarios,
AffCom(14), No. 1, January 2023, pp. 747-760.
IEEE DOI 2303
Solid modeling, Emotion recognition, Safety, Task analysis, Intelligent vehicles, Vehicle dynamics, Physiology, Driving safety, intelligent vehicles BibRef

Xu, J.W.[Jia-Wei], Pan, S.C.[Si-Cheng], Sun, P.Z.H.[Poly Z. H.], Park, S.H.[Seop Hyeong], Guo, K.[Kun],
Human-Factors-in-Driving-Loop: Driver Identification and Verification via a Deep Learning Approach using Psychological Behavioral Data,
ITS(24), No. 3, March 2023, pp. 3383-3394.
IEEE DOI 2303
Vehicles, Behavioral sciences, Deep learning, Data models, Sensors, Global Positioning System, Smart phones, human factors in driving loop BibRef

Alsaid, A.[Areen], Lee, J.D.[John D.], Noejovich, S.I.[Sofia I.], Chehade, A.[Abdallah],
The Effect of Vehicle Automation Styles on Drivers' Emotional State,
ITS(24), No. 4, April 2023, pp. 3963-3973.
IEEE DOI 2304
Automation, Vehicles, Monitoring, Modeling, Emotion recognition, Behavioral sciences, Affective computing, Video analysis, multilevel Bayesian modeling BibRef

Jain, D.K.[Deepak Kumar], Dutta, A.K.[Ashit Kumar], Verdú, E.[Elena], Alsubai, S.[Shtwai], Sait, A.R.W.[Abdul Rahaman Wahab],
An automated hyperparameter tuned deep learning model enabled facial emotion recognition for autonomous vehicle drivers,
IVC(133), 2023, pp. 104659.
Elsevier DOI 2305
Autonomous driving systems, Emotion recognition, Deep learning, Facial expressions, Object detection, Metaheuristics BibRef

Kumar, R.P.[Rahul Prasanna], Melcher, D.[David], Buttolo, P.[Pietro], Jia, Y.[Yunyi],
Tracking Occupant Activities in Autonomous Vehicles Using Capacitive Sensing,
ITS(24), No. 7, July 2023, pp. 6800-6819.
IEEE DOI 2307
Capacitance, Sensors, Hidden Markov models, Autonomous vehicles, Capacitance measurement, Feature extraction, recurrent neural networks BibRef

Hu, C.H.[Chang-Hui], Liu, Y.[Yu], Xu, L.T.[Lin-Tao], Jing, X.Y.[Xiao-Yuan], Lu, X.B.[Xiao-Bo], Yang, W.K.[Wan-Kou], Liu, P.[Pan],
Joint Image-to-Image Translation for Traffic Monitoring Driver Face Image Enhancement,
ITS(24), No. 8, August 2023, pp. 7961-7973.
IEEE DOI 2308
Degradation, Face recognition, Faces, Vehicles, Monitoring, Image edge detection, Training, Joint image-to-image translation, traffic monitoring driver face image BibRef

Chai, W.H.[Wei-Heng], Chen, J.J.[Jia-Jing], Wang, J.[Jiyang], Velipasalar, S.[Senem], Venkatachalapathy, A.[Archana], Adu-Gyamfi, Y.[Yaw], Merickel, J.[Jennifer], Sharma, A.[Anuj],
Driver Head Pose Detection From Naturalistic Driving Data,
ITS(24), No. 9, September 2023, pp. 9368-9377.
IEEE DOI 2310
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Bang, J.S.[Ji-Seon], Won, D.O.[Dong-Ok], Kam, T.E.[Tae-Eui], Lee, S.W.[Seong-Whan],
Motion Sickness Prediction Based on Dry EEG in Real Driving Environment,
ITS(24), No. 5, May 2023, pp. 5442-5455.
IEEE DOI 2305
Electroencephalography, Vehicles, Motion sickness, Feature extraction, Brain modeling, Automobiles, Automation, convolutional neural network BibRef

Ko, K.L.[Kwang-Lim], Yoo, J.S.[Jun-Sang], Han, C.W.[Chang-Woo], Kim, J.[Jungyeop], Jung, S.W.[Seung-Won],
Pose and Shape Estimation of Humans in Vehicles,
ITS(25), No. 1, January 2024, pp. 402-416.
IEEE DOI 2402
Shape, Three-dimensional displays, Pose estimation, Monitoring, Annotations, Training, Cameras, Deep learning, shape estimation BibRef

Govers, W.[Wim], Yurtman, A.[Aras], Aslandere, T.[Turgay], Eikelenberg, N.[Nicole], Meert, W.[Wannes], Davis, J.[Jesse],
Time-Shifted Transformers for Driver Identification Using Vehicle Data,
ITS(25), No. 5, May 2024, pp. 3767-3776.
IEEE DOI 2405
Vehicles, Time series analysis, Transformers, Sensors, Computer architecture, Behavioral sciences, Task analysis, multivariate time series BibRef

Karas, V.[Vincent], Schuller, D.M.[Dagmar M.], Schuller, B.W.[Björn W.],
Audiovisual Affect Recognition for Autonomous Vehicles: Applications and Future Agendas,
ITS(25), No. 6, June 2024, pp. 4918-4932.
IEEE DOI 2406
Vehicles, Automobiles, Monitoring, Cameras, Autonomous vehicles, Intelligent sensors, Autonomous vehicles, interior sensing, emotion recognition BibRef

Angkan, P.[Prithila], Behinaein, B.[Behnam], Mahmud, Z.[Zunayed], Bhatti, A.[Anubhav], Rodenburg, D.[Dirk], Hungler, P.[Paul], Etemad, A.[Ali],
Multimodal Brain-Computer Interface for In-Vehicle Driver Cognitive Load Measurement: Dataset and Baselines,
ITS(25), No. 6, June 2024, pp. 5949-5964.
IEEE DOI 2406
Cognitive load, Task analysis, Vehicles, Physiology, Electroencephalography, Load modeling, Electrocardiography, Driver, deep learning BibRef

Gharamohammadi, A.[Ali], Dabak, A.G.[Anand G.], Yang, Z.G.[Zi-Gang], Khajepour, A.[Amir], Shaker, G.[George],
Volume-Based Occupancy Detection for In-Cabin Applications by Millimeter Wave Radar,
RS(16), No. 16, 2024, pp. 3068.
DOI Link 2408
Is the child in the vehicle. BibRef

Hasan, M.D.T.[M.D. Tanim], Alghamdi, H.[Huda], Taamneh, S.[Salah], Manser, M.[Mike], Wunderlich, R.[Robert], Tsiamyrtzis, P.[Panagiotis], Pavlidis, I.[Ioannis],
Investigating Cardiovascular Activation of Young Adults in Routine Driving,
AffCom(15), No. 3, July 2024, pp. 769-786.
IEEE DOI 2409
Vehicles, Behavioral sciences, Smart phones, Biomedical monitoring, Heart rate, Automobiles, Accidents, Affective computing, trait anxiety BibRef

Xu, Z.[Zhuoyan], Xu, J.[Jingke],
GR-Former: Graph-reinforcement transformer for skeleton-based driver action recognition,
IET-CV(18), No. 7, 2024, pp. 982-991.
DOI Link 2411
pose estimation BibRef

Gao, Q.[Qi], He, D.[Di], Xu, G.L.[Gui-Lin],
Improving YOLOv8 with parallel frequency channel attention for taxi passengers,
IET-IPR(18), No. 13, 2024, pp. 4422-4431.
DOI Link 2411
convolutional neural nets, object detection BibRef

Kim, S.H.[Seo-Hee], Jung, E.[Eunseo], Shin, H.[Hyojin], Yang, I.B.[In-Beom], Woo, J.Y.[Ji-Young],
Boosting Weak Learners With Multi-Agent Reinforcement Learning for Enhanced Stacking Models: An Application on Driver Emotion Classification,
ITS(25), No. 12, December 2024, pp. 20478-20492.
IEEE DOI 2412
Brain modeling, Vehicles, Biological system modeling, Reinforcement learning, Stacking, Electroencephalography, driver emotion detection BibRef

Pang, J.[Junbiao], Sabir, M.A.[Muhammad Ayub], Wang, Z.[Zuyun], Hu, A.[Anjing], Yang, X.[Xue], Yu, H.T.[Hai-Tao], Huang, Q.M.[Qing-Ming],
Finding a Taxi With Illegal Driver Substitution Activity via Behavior Modelings,
ITS(25), No. 12, December 2024, pp. 20309-20319.
IEEE DOI 2412
Public transportation, Global Positioning System, Vehicles, Feature extraction, Trajectory, Object recognition, pooling BibRef

Fu, F.J.[Feng-Jie], Cai, Z.[Zhenegyi], Jin, S.[Sheng], Xu, C.[Cheng],
Monitoring ride-hailing passenger security risk: An approach using human geography data,
IET-ITS(19), No. 1, 2025, pp. e12601.
DOI Link 2501
big data, global positioning system, pattern clustering, risk analysis, security BibRef

Zhou, G.L.[Gui-Liang], Xu, K.W.[Kai-Wen], Chen, J.[Jian], Mao, L.[Lina],
Identifying abnormal driving states of drunk drivers using UAV,
IET-ITS(19), No. 1, 2025, pp. e12608.
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traffic, transportation BibRef

Zhang, H.[Hongpu], Cui, Z.[Zhe], Su, F.[Fei],
A Coarse-to-fine Two-stage Helmet Detection Method for Motorcyclists,
AICity24(7066-7074)
IEEE DOI 2410
Visualization, Head, Target tracking, Urban areas, Motorcycles, Detectors, Safety, Motorcyclist Helmet Detection, Object Detection BibRef

Luong, T.V.[Thien Van], Nguyen, H.S.P.[Huu Si Phuc], Dinh, D.K.[Duy Khanh], Duong, V.H.[Viet Hung], Vo, D.H.S.[Duy Hong Sam], Vu, H.[Huan], Hoang, M.T.[Minh Tuan], Nguyen, T.C.[Tien Cuong],
Motorcyclist Helmet Violation Detection Framework by Leveraging Robust Ensemble and Augmentation Methods,
AICity24(7027-7036)
IEEE DOI 2410
Deep learning, Head, Urban areas, Transportation, Motorcycles, Object detection, Data augmentation BibRef

Chen, Y.[Yunliang], Zhou, W.[Wei], Zhou, Z.[Zicen], Ma, B.[Bing], Wang, C.[Chen], Shang, Y.[Yingda], Guo, A.[An], Chu, T.S.[Tian-Shu],
An Effective Method for Detecting Violation of Helmet Rule for Motorcyclists,
AICity24(7085-7090)
IEEE DOI 2410
Training, Head, Computational modeling, Urban areas, Motorcycles, Transformers, Video surveillance BibRef

Vo, H.[Hao], Tran, S.[Sieu], Nguyen, D.M.[Duc Minh], Nguyen, T.[Thua], Do, T.[Tien], Le, D.D.[Duy-Dinh], Ngo, T.D.[Thanh Duc],
Robust Motorcycle Helmet Detection in Real-World Scenarios: Using Co-DETR and Minority Class Enhancement,
AICity24(7163-7171)
IEEE DOI 2410
Head, Navigation, Urban areas, Motorcycles, Lighting, Object detection, Safety BibRef

Dong, Z.[Zhekang], Hu, C.H.[Chen-Hao], Zhou, S.Q.[Shi-Qi], Zhu, L.Y.[Li-Yan], Wang, J.[Junfan], Chen, Y.[Yi], Lv, X.D.[Xu-Dong], Ji, X.Y.[Xiao-Yue],
DECNet: A Non-Contacting Dual-Modality Emotion Classification Network for Driver Health Monitoring,
CVPM24(371-379)
IEEE DOI Code:
WWW Link. 2410
Smart cities, Pressing, Feature extraction, Multitasking, Road safety, Safety BibRef

Agrawal, D.[Deeksha], Tapaswi, S.[Shashikala],
Identifying Occurrences of Abnormal and Drunk Driving Using Smartphones,
ICCVMI23(1-9)
IEEE DOI 2403
Radio frequency, Drugs, Roads, Machine learning, Prediction algorithms, Automobiles, Vehicle dynamics, accelerometer data BibRef

Saadi, I.[Ibtissam], Cunningham, D.W.[Douglas W.], Abdelmalik, T.A.[Taleb-Ahmed], Hadid, A.[Abdenour], El Hillali, Y.[Yassin],
Driver's Facial Expression Recognition Using Global Context Vision Transformer,
ICCVMI23(1-8)
IEEE DOI 2403
Emotion recognition, Head, Face recognition, Lighting, Transformers, Feature extraction, Data augmentation, global context vision transformer BibRef

Wang, X.F.[Xiao-Feng], Zhu, Z.[Zheng], Xu, W.B.[Wen-Bo], Zhang, Y.P.[Yun-Peng], Wei, Y.[Yi], Chi, X.[Xu], Ye, Y.[Yun], Du, D.L.[Da-Long], Lu, J.W.[Ji-Wen], Wang, X.G.[Xin-Gang],
OpenOccupancy: A Large Scale Benchmark for Surrounding Semantic Occupancy Perception,
ICCV23(17804-17813)
IEEE DOI 2401
E.g. driver. BibRef

Guo, Y.[Yuyu], Bai, Y.C.[Yan-Cheng], Shi, D.[Daiqi], Cai, Y.[Yang], Bian, W.[Wei],
DPOSE: Online Keypoint-CAM Guided Inference for Driver Pose Estimation with GMM-based Balanced Sampling,
Precognition23(3656-3665)
IEEE DOI 2309
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Ma, Y.S.[Yun-Sheng], Yuan, L.Q.[Liang-Qi], Abdelraouf, A.[Amr], Han, K.T.[Kyung-Tae], Gupta, R.[Rohit], Li, Z.H.[Zi-Hao], Wang, Z.[Ziran],
M2DAR: Multi-View Multi-Scale Driver Action Recognition with Vision Transformer,
AICity23(5287-5294)
IEEE DOI 2309
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Ma, Y.M.[Yi-Ming], Sanchez, V.[Victor], Nikan, S.[Soodeh], Upadhyay, D.[Devesh], Atote, B.[Bhushan], Guha, T.[Tanaya],
Robust Multiview Multimodal Driver Monitoring System Using Masked Multi-Head Self-Attention,
MULA23(2617-2625)
IEEE DOI 2309
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Cui, S.[Shun], Zhang, T.T.[Tian-Tian], Sun, H.[Hao], Zhou, X.Y.[Xu-Yang], Yu, W.Q.[Wen-Qing], Zhen, A.G.[Ai-Gong], Wu, Q.H.[Qi-Hang], He, Z.J.[Zhong-Jiang],
An Effective Motorcycle Helmet Object Detection Framework for Intelligent Traffic Safety,
AICity23(5470-5476)
IEEE DOI 2309
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Wang, B.S.[Bor-Shiun], Chen, P.Y.[Ping-Yang], Hsieh, Y.K.[Yi-Kuan], Hsieh, J.W.[Jun-Wei], Chang, M.C.[Ming-Ching], He, J.[JiaXin], Teng, S.Y.[Shin-You], Yue, H.[HaoYuan], Tseng, Y.C.[Yu-Chee],
PRB-FPN+: Video Analytics for Enforcing Motorcycle Helmet Laws,
AICity23(5477-5485)
IEEE DOI 2309
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Tran, D.N.N.[Duong Nguyen-Ngoc], Pham, L.H.[Long Hoang], Jeon, H.J.[Hyung-Joon], Nguyen, H.H.[Huy-Hung], Jeon, H.M.[Hyung-Min], Tran, T.H.P.[Tai Huu-Phuong], Jeon, J.W.[Jae Wook],
Robust Automatic Motorcycle Helmet Violation Detection for an Intelligent Transportation System,
AICity23(5341-5349)
IEEE DOI 2309
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Aboah, A.[Armstrong], Wang, B.[Bin], Bagci, U.[Ulas], Adu-Gyamfi, Y.[Yaw],
Real-time Multi-Class Helmet Violation Detection Using Few-Shot Data Sampling Technique and YOLOv8,
AICity23(5350-5358)
IEEE DOI 2309
BibRef

Tsai, C.M.[Chun-Ming], Hsieh, J.W.[Jun-Wei], Chang, M.C.[Ming-Ching], He, G.L.[Guan-Lin], Chen, P.Y.[Ping-Yang], Chang, W.T.[Wei-Tsung], Hsieh, Y.K.[Yi-Kuan],
Video Analytics for Detecting Motorcyclist Helmet Rule Violations,
AICity23(5366-5374)
IEEE DOI 2309
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Duong, V.H.[Viet Hung], Tran, Q.H.[Quang Huy], Nguyen, H.S.P.[Huu Si Phuc], Nguyen, D.Q.[Duc Quyen], Nguyen, T.C.[Tien Cuong],
Helmet Rule Violation Detection for Motorcyclists using a Custom Tracking Framework and Advanced Object Detection Techniques,
AICity23(5381-5390)
IEEE DOI 2309
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Zheng, J.X.[Jing-Xiao], Shi, X.W.[Xin-Wei], Gorban, A.[Alexander], Mao, J.H.[Jun-Hua], Song, Y.[Yang], Qi, C.R.[Charles R.], Liu, T.[Ting], Chari, V.[Visesh], Cornman, A.[Andre], Zhou, Y.[Yin], Li, C.C.[Cong-Cong], Anguelov, D.[Dragomir],
Multi-modal 3D Human Pose Estimation with 2D Weak Supervision in Autonomous Driving,
WAD22(4477-4486)
IEEE DOI 2210
Point cloud compression, Solid modeling, Image segmentation, Laser radar, Pose estimation, Virtual reality BibRef

Liang, J.W.[Jun-Wei], Zhu, H.[He], Zhang, E.[Enwei], Zhang, J.[Jun],
Stargazer: A Transformer-based Driver Action Detection System for Intelligent Transportation,
AICity22(3159-3166)
IEEE DOI 2210
Location awareness, Roads, Urban areas, Transformer cores, Transformers, Behavioral sciences BibRef

Vats, A.[Arpita], Anastasiu, D.C.[David C.],
Key Point-Based Driver Activity Recognition,
AICity22(3273-3280)
IEEE DOI 2210
Conferences, Urban areas, Pose estimation, Activity recognition, Predictive models, Feature extraction BibRef

Hossain, M.I.[Md. Iqbal], Muhib, R.B.[Raghib Barkat], Chakrabarty, A.[Amitabha],
Identifying Bikers Without Helmets Using Deep Learning Models,
DICTA21(01-08)
IEEE DOI 2201
Deep learning, Head, Surveillance, Computational modeling, Object detection, Real-time systems, Surveillance System, Object Detection BibRef

Lin, H.[Hanhe], Chen, G.[Guangan], Siebert, F.W.[Felix Wilhelm],
Positional Encoding: Improving Class-Imbalanced Motorcycle Helmet use Classification,
ICIP21(1194-1198)
IEEE DOI 2201
Training, Head, Image coding, Motorcycles, Transforms, Object detection, Road safety, Helmet use, image classification, motorcycle safety BibRef

Guesdon, R.[Romain], Crispim-Junior, C.[Carlos], Tougne, L.[Laure],
DriPE: A Dataset for Human Pose Estimation in Real-World Driving Settings,
AVVision21(2865-2874)
IEEE DOI 2112
Measurement, Deep learning, Pose estimation, Road vehicles, Lighting BibRef

Köpüklü, O.[Okan], Zheng, J.P.[Jia-Peng], Xu, H.[Hang], Rigoll, G.[Gerhard],
Driver Anomaly Detection: A Dataset and Contrastive Learning Approach,
WACV21(91-100)
IEEE DOI 2106
Training, Measurement, Benchmark testing, Task analysis, Anomaly detection, Monitoring BibRef

Wharton, Z.[Zachary], Behera, A.[Ardhendu], Liu, Y.H.[Yong-Huai], Bessis, N.[Nik],
Coarse Temporal Attention Network (CTA-Net) for Driver's Activity Recognition,
WACV21(1278-1288)
IEEE DOI 2106
Visualization, Network topology, Focusing, Activity recognition, Topology, Spatiotemporal phenomena, Task analysis BibRef

Rundo, F.[Francesco], Trenta, F.[Francesca], Leotta, R.[Roberto], Spampinato, C.[Concetto], Piuri, V.[Vincenzo], Conoci, S.[Sabrina], Labati, R.D.[Ruggero Donida], Scotti, F.[Fabio], Battiato, S.[Sebastiano],
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Kandeel, A.A.[Amany A.], Abbas, H.M.[Hazem M.], Hassanein, H.S.[Hossam S.],
Explainable Model Selection of a Convolutional Neural Network for Driver's Facial Emotion Identification,
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Activity-aware Attributes for Zero-Shot Driver Behavior Recognition,
VL3W20(3950-3955)
IEEE DOI 2008
Semantics, Vehicles, Benchmark testing, Task analysis, Feature extraction, Visualization, Training BibRef

da Cruz, S.D.[Steve Dias], Wasenmüller, O.[Oliver], Beise, H.P.[Hans-Peter], Stifter, T.[Thomas], Stricker, D.[Didier],
SVIRO: Synthetic Vehicle Interior Rear Seat Occupancy Dataset and Benchmark,
WACV20(962-971)
IEEE DOI 2006
Dataset, Vehicle Surveilance.
WWW Link. Task analysis, Benchmark testing, Training, Automobiles, Cameras, Lightning BibRef

Chairat, A., Dailey, M.N.[Matthew N.], Limsoonthrakul, S., Ekpanyapong, M.[Mongkol],
Low Cost, High Performance Automatic Motorcycle Helmet Violation Detection,
WACV20(3549-3557)
IEEE DOI 2006
Motorcycles, Training, Cameras, Roads, Graphics processing units, Law enforcement, Neural networks BibRef

Chun, S., Ghalehjegh, N.H., Choi, J., Schwarz, C., Gaspar, J., McGehee, D., Baek, S.,
NADS-Net: A Nimble Architecture for Driver and Seat Belt Detection via Convolutional Neural Networks,
ADW19(2413-2421)
IEEE DOI 2004
convolutional neural nets, driver information systems, feature extraction, mobile robots, object detection, Seat Belt Detection BibRef

Rangesh, A., Trivedi, M.M.,
Forced Spatial Attention for Driver Foot Activity Classification,
ACVR19(2514-2521)
IEEE DOI 2004
entropy, image classification, learning (artificial intelligence), Driver Safety BibRef

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Behera, A.[Ardhendu], Keidel, A.[Alexander], Debnath, B.[Bappaditya],
Context-driven Multi-stream LSTM (M-LSTM) for Recognizing Fine-Grained Activity of Drivers,
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Miyamoto, S.,
Passenger in vehicle counting method of HOV/HOT system,
ICPR18(1536-1541)
IEEE DOI 1812
Face detection, Cameras, Face, Algorithms, Image processing, Streaming media, Dispatching, number of passenger in vehicle, HOT BibRef

Artan, Y.[Yusuf], Balci, B.[Burak], Elihos, A.[Alperen], Alkan, B.[Bensu],
Vision Based Driver Smoking Behavior Detection Using Surveillance Camera Images,
CIAP19(II:468-476).
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Earlier: A2, A4, A3, A1:
Front Seat Child Occupancy Detection Using Road Surveillance Camera Images,
ICIP18(1927-1931)
IEEE DOI 1809
Face, Automotive components, Detectors, Face detection, Task analysis, Cameras, Machine learning, Traffic Enforcement, Image Classification BibRef

Majdi, M.S., Ram, S., Gill, J.T., Rodríguez, J.J.,
Drive-Net: Convolutional Network for Driver Distraction Detection,
Southwest18(1-4)
IEEE DOI 1809
Forestry, Training, Vehicles, Vegetation, Cameras, Neural networks, Image classification, driver distraction BibRef

Xue, Q.[Qing], Sun, J.W.[Jia-Wei], Hao, J.[Jia], Liu, M.[Minxia],
The Research on Layout and Simulation of Human-Machine Interface in Vehicle,
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Mapping System Between Passenger Experience and the Factors of Aircraft Cabin Design,
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Derman, E., Salah, A.A.,
Continuous Real-Time Vehicle Driver Authentication Using Convolutional Neural Network Based Face Recognition,
FG18(577-584)
IEEE DOI 1806
Authentication, Automobiles, Cameras, Face, Feature extraction, Videos, convolutional neural network, driver authentication, real time face verification BibRef

Tu, I.[Ian], Bhalerao, A.[Abhir], Griffiths, N.[Nathan], Delgado, M.[Mauricio], Popham, T.[Thomas], Mouzakitis, A.[Alex],
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Cost-Based Feature Transfer for Vehicle Occupant Classification,
CVTSV16(I: 405-419).
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Yamada, K.[Keiichi], Mitani, T.[Tomonori],
Estimating Driver Awareness of Crossing Pedestrians While Turning Left Based on Vehicle Behavior Using Bayesian Approach,
ICPR14(1898-1903)
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Bayes methods BibRef

Brun, L.[Luc], Cappellania, B.[Benito], Saggese, A.[Alessia], Vento, M.[Mario],
Detection of anomalous driving behaviors by unsupervised learning of graphs,
AVSS14(405-410)
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Clustering algorithms BibRef

Artan, Y.[Yusuf], Paul, P.[Peter], Perronin, F.[Florent], Burry, A.[Aaron],
Comparison of face detection and image classification for detecting front seat passengers in vehicles,
WACV14(1006-1012)
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Cameras BibRef

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Empty Vehicle Detection with Video Analytics,
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Hao, X.L.[Xiao-Li], Chen, H.J.[Hou-Jin], Yao, C.[Chang], Yang, N.[Na], Bi, H.J.[Hong-Jun], Wang, C.L.[Chang-Li],
A near-infrared imaging method for capturing the interior of a vehicle through windshield,
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Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Driver Monitoring, Mobile Phone Usage .