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Home  | Behavioral  | Applications  | Datasets  

Scene gaze  | In-vehicle gaze  | Distraction detection  | Drowsiness detection  | Action anticipation  | Driver awareness  | Self-driving  | Papers with code  


Click on each entry below to see additional information.

    Yang et al., Quantitative Identification of Driver Distraction: A Weakly Supervised Contrastive Learning Approach, Trans. ITS, 2024 | paper | code
      @article{2024_T-ITS_Yang,
          author = "Yang, Haohan and Liu, Haochen and Hu, Zhongxu and Nguyen, Anh-Tu and Guerra, Thierry-Marie and Lv, Chen",
          journal = "IEEE Transactions on Intelligent Transportation Systems",
          publisher = "IEEE",
          title = "Quantitative identification of driver distraction: A weakly supervised contrastive learning approach",
          year = "2023"
      }
      
    Li et al., Domain Adaptive Driver Distraction Detection Based on Partial Feature Alignment and Confusion-Minimized Classification, Trans. ITS, 2024 | paper
      @article{2024_T-ITS_Li,
          author = "Li, Guofa and Wang, Guanglei and Guo, Zizheng and Liu, Qing and Luo, Xiyuan and Yuan, Bangwei and Li, Mingrui and Yang, Lu",
          journal = "IEEE Transactions on Intelligent Transportation Systems",
          publisher = "IEEE",
          title = "Domain Adaptive Driver Distraction Detection Based on Partial Feature Alignment and Confusion-Minimized Classification",
          year = "2024"
      }
      
    Hasan et al., Vision-Language Models Can Identify Distracted Driver Behavior From Naturalistic Videos, Trans. ITS, 2024 | paper | code
      @article{2024_T-ITS_Hasan,
          author = "Hasan, Md Zahid and Chen, Jiajing and Wang, Jiyang and Rahman, Mohammed Shaiqur and Joshi, Ameya and Velipasalar, Senem and Hegde, Chinmay and Sharma, Anuj and Sarkar, Soumik",
          journal = "IEEE Transactions on Intelligent Transportation Systems",
          publisher = "IEEE",
          title = "Vision-language models can identify distracted driver behavior from naturalistic videos",
          year = "2024"
      }
      
    Chai et al., Rethinking the Evaluation of Driver Behavior Analysis Approaches, Trans. ITS, 2024 | paper
      @article{2024_T-ITS_Chai,
          author = "Chai, Weiheng and Wang, Jiyang and Chen, Jiajing and Velipasalar, Senem and Sharma, Anuj",
          journal = "IEEE Transactions on Intelligent Transportation Systems",
          publisher = "IEEE",
          title = "Rethinking the Evaluation of Driver Behavior Analysis Approaches",
          year = "2024"
      }
      
    Pizarro et al., DRVMon-VM: Distracted driver recognition using large pre-trained video transformers, IV, 2024 | paper
      @inproceedings{2024_IV_Pizarro,
          author = "Pizarro, Ricardo and Bergasa, Luis M and Baumela, Luis and Buenaposada, Jos{\'e} M and Barea, Rafael",
          booktitle = "2024 IEEE Intelligent Vehicles Symposium (IV)",
          organization = "IEEE",
          pages = "1901--1906",
          title = "DRVMon-VM: Distracted driver recognition using large pre-trained video transformers",
          year = "2024"
      }
      
    Palo et al., Holistic Driver Monitoring: A Multi-Task Approach for In-Cabin Driver Attention Evaluation through Multi-Camera Data, IV, 2024 | paper
      Dataset(s): DMD
      @inproceedings{2024_IV_Palo,
          author = "Palo, Patitapaban and Nayak, Satyajit and Modhugu, Durga Nagendra Raghava Kumar and Gupta, Kwanit and Uttarkabat, Satarupa",
          booktitle = "2024 IEEE Intelligent Vehicles Symposium (IV)",
          organization = "IEEE",
          pages = "1361--1366",
          title = "Holistic Driver Monitoring: A Multi-Task Approach for In-Cabin Driver Attention Evaluation through Multi-Camera Data",
          year = "2024"
      }
      
    Ma et al., ViT-DD: Multi-Task Vision Transformer for Semi-Supervised Driver Distraction Detection, IV, 2024 | paper | code
      @inproceedings{2024_IV_Ma,
          author = "Ma, Yunsheng and Wang, Ziran",
          booktitle = "2024 IEEE Intelligent Vehicles Symposium (IV)",
          organization = "IEEE",
          pages = "417--423",
          title = "Vit-dd: Multi-task vision transformer for semi-supervised driver distraction detection",
          year = "2024"
      }
      
    Mittal et al., CAT-CapsNet: A Convolutional and Attention Based Capsule Network to Detect the Driver’s Distraction, Trans. ITS, 2023 | paper
      Dataset(s): AUCD2, Statefarm
      @article{2023_T-ITS_Mittal,
          author = "Mittal, Himanshu and Verma, Bindu",
          journal = "IEEE Transactions on Intelligent Transportation Systems",
          publisher = "IEEE",
          title = "CAT-CapsNet: A Convolutional and Attention Based Capsule Network to Detect the Driver’s Distraction",
          year = "2023"
      }
      
    Mittal et al., CAT-CapsNet: A Convolutional and Attention Based Capsule Network to Detect the Driver’s Distraction, Trans. ITS, 2023 | paper
      @article{2023_T-ITS_Mittal,
          author = "Mittal, Himanshu and Verma, Bindu",
          journal = "IEEE Transactions on Intelligent Transportation Systems",
          publisher = "IEEE",
          title = "CAT-CapsNet: A Convolutional and Attention Based Capsule Network to Detect the Driver’s Distraction",
          year = "2023"
      }
      
    Kuang et al., MIFI: MultI-Camera Feature Integration for Robust 3D Distracted Driver Activity Recognition, Trans. ITS, 2023 | paper
      @article{2023_T-ITS_Kuang,
          author = "Kuang, Jian and Li, Wenjing and Li, Fang and Zhang, Jun and Wu, Zhongcheng",
          journal = "IEEE Transactions on Intelligent Transportation Systems",
          publisher = "IEEE",
          title = "MIFI: MultI-Camera Feature Integration for Robust 3D Distracted Driver Activity Recognition",
          year = "2023"
      }
      
    Sonth et al., Explainable Driver Activity Recognition Using Video Transformer in Highly Automated Vehicle, IV, 2023 | paper | code
      Dataset(s): VTTIMLP01, SHRP2
      @inproceedings{2023_IV_Sonth,
          author = "Sonth, Akash and Sarkar, Abhijit and Bhagat, Hirva and Abbott, Lynn",
          booktitle = "2023 IEEE Intelligent Vehicles Symposium (IV)",
          organization = "IEEE",
          pages = "1--8",
          title = "Explainable Driver Activity Recognition Using Video Transformer in Highly Automated Vehicle",
          year = "2023"
      }
      
    Morales-Alvarez et al., On Transferability of Driver Observation Models from Simulated to Real Environments in Autonomous Cars, ITSC, 2023 | paper
      @inproceedings{2023_ITSC_Morales-Alvarez,
          author = "Morales-Alvarez, Walter and Certad, Novel and Roitberg, Alina and Stiefelhagen, Rainer and Olaverri-Monreal, Cristina",
          booktitle = "2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)",
          organization = "IEEE",
          pages = "3129--3134",
          title = "On Transferability of Driver Observation Models from Simulated to Real Environments in Autonomous Cars",
          year = "2023"
      }
      
    Hamieh et al., Driver Visual Distraction Detection Using Unsupervised Learning Techniques, ITSC, 2023 | paper
      Dataset(s): private
      @inproceedings{2023_ITSC_Hamieh,
          author = "Hamieh, Salam and Heiries, Vincent and Al-Osman, Hussein and Godin, Christelle and Aloui, Saifeddine",
          booktitle = "2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)",
          organization = "IEEE",
          pages = "945--950",
          title = "Driver Visual Distraction Detection Using Unsupervised Learning Techniques",
          year = "2023"
      }
      
    Zhou et al., Multi View Action Recognition for Distracted Driver Behavior Localization, CVPRW, 2023 | paper | code
      @inproceedings{2023_CVPRW_Zhou,
          author = "Zhou, Wei and Qian, Yinlong and Jie, Zequn and Ma, Lin",
          booktitle = "Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition",
          pages = "5375--5380",
          title = "Multi view action recognition for distracted driver behavior localization",
          year = "2023"
      }
      
    Du et al., A Multimodal Fusion Fatigue Driving Detection Method Based on Heart Rate and PERCLOS, Trans. ITS, 2022 | paper
      @article{2022_T-ITS_Du,
          author = "Du, Guanglong and Zhang, Linlin and Su, Kang and Wang, Xueqian and Teng, Shaohua and Liu, Peter X",
          journal = "Ieee Transactions on Intelligent Transportation Systems",
          number = "11",
          pages = "21810--21820",
          publisher = "IEEE",
          title = "A multimodal fusion fatigue driving detection method based on heart rate and PERCLOS",
          volume = "23",
          year = "2022"
      }
      
    Doshi et al., Federated Learning-based Driver Activity Recognition for Edge Devices, CVPRW, 2022 | paper
      @inproceedings{2022_CVPRW_Doshi,
          author = "Doshi, Keval and Yilmaz, Yasin",
          booktitle = "Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition",
          pages = "3338--3346",
          title = "Federated learning-based driver activity recognition for edge devices",
          year = "2022"
      }
      
    Ding et al., A Coarse-to-Fine Boundary Localization method for Naturalistic Driving Action Recognition, CVPRW, 2022 | paper
      @article{2022_CVPRW_Ding,
          author = "Du, Guanglong and Zhang, Linlin and Su, Kang and Wang, Xueqian and Teng, Shaohua and Liu, Peter X",
          journal = "Ieee Transactions on Intelligent Transportation Systems",
          number = "11",
          pages = "21810--21820",
          publisher = "IEEE",
          title = "A multimodal fusion fatigue driving detection method based on heart rate and PERCLOS",
          volume = "23",
          year = "2022"
      }
      
    Alyahya et al., Temporal Driver Action Localization using Action Classification Methods, CVPRW, 2022 | paper
      @inproceedings{2022_CVPRW_Alyahya,
          author = "Alyahya, Munirah and Alghannam, Shahad and Alhussan, Taghreed",
          booktitle = "Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition",
          pages = "3319--3326",
          title = "Temporal Driver Action Localization using Action Classification Methods",
          year = "2022"
      }
      
    Kopuklu et al., Driver Anomaly Detection: A Dataset and Contrastive Learning Approach, WACV, 2021 | paper
      Dataset(s): DAD
      @inproceedings{2021_WACV_Kopuklu,
          author = "Kopuklu, Okan and Zheng, Jiapeng and Xu, Hang and Rigoll, Gerhard",
          booktitle = "Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision",
          pages = "91--100",
          title = "Driver anomaly detection: A dataset and contrastive learning approach",
          year = "2021"
      }
      
    Huang et al., Driver Distraction Detection Based on the True Driver’s Focus of Attention, Trans. ITS, 2021 | paper
      @article{2021_T-ITS_Huang,
          author = "Huang, Jianling and Long, Yan and Zhao, Xiaohua",
          journal = "IEEE Transactions on Intelligent Transportation Systems",
          publisher = "IEEE",
          title = "Driver Glance Behavior Modeling Based on Semi-Supervised Clustering and Piecewise Aggregate Representation",
          year = "2021"
      }
      
    Chen et al., Fine-Grained Detection of Driver Distraction Based on Neural Architecture Search, Trans. ITS, 2021 | paper
      @article{2021_T-ITS_Chen,
          author = "Chen, Jie and Jiang, YaNan and Huang, ZhiXiang and Guo, XiaoHui and Wu, BoCai and Sun, Long and Wu, Tao",
          journal = "IEEE Transactions on Intelligent Transportation Systems",
          title = "Fine-Grained Detection of Driver Distraction Based on Neural Architecture Search",
          year = "2021"
      }
      
    Yang et al., Recognition of visual-related non-driving activities using a dual-camera monitoring system, PR, 2021 | paper
      Dataset(s): private
      @article{2021_PR_Yang,
          author = "Yang, Lichao and Dong, Kuo and Ding, Yan and Brighton, James and Zhan, Zhenfei and Zhao, Yifan",
          journal = "Pattern Recognition",
          pages = "107955",
          title = "Recognition of visual-related non-driving activities using a dual-camera monitoring system",
          volume = "116",
          year = "2021"
      }
      
    Yang et al., Recognition of visual-related non-driving activities using a dual-camera monitoring system, Pattern Recognition, 2021 | paper
      Dataset(s): private
      @article{2021_PR_Yang,
          author = "Yang, Lichao and Dong, Kuo and Ding, Yan and Brighton, James and Zhan, Zhenfei and Zhao, Yifan",
          journal = "Pattern Recognition",
          pages = "107955",
          title = "Recognition of visual-related non-driving activities using a dual-camera monitoring system",
          volume = "116",
          year = "2021"
      }
      
    Tran et al., Real-time Detection of Distracted Driving using Dual Cameras, IROS, 2020 | paper
      Dataset(s): private
      @inproceedings{2020_IROS_Tran,
          author = "Tran, Duy and Do, Ha Manh and Lu, Jiaxing and Sheng, Weihua",
          booktitle = "IROS",
          title = "Real-time Detection of Distracted Driving using Dual Cameras",
          year = "2020"
      }
      
    Fan et al., GazMon: Eye Gazing Enabled Driving Behavior Monitoring and Prediction, IEEE Transactions on Mobile Computing, 2019 | paper
      Dataset(s): private
      @article{2019_TMC_Fan,
          author = "Fan, Xiaoyi and Wang, Feng and Song, Danyang and Lu, Yuhe and Liu, Jiangchuan",
          journal = "IEEE Transactions on Mobile Computing",
          title = "{GazMon: Eye Gazing Enabled Driving Behavior Monitoring and Prediction}",
          year = "2019"
      }
      
    Chiou et al., Driver Monitoring Using Sparse Representation With Part-Based Temporal Face Descriptors, Trans. ITS, 2019 | paper
      @article{2019_T-ITS_Chiou,
          author = "Chiou, Chien-Yu and Wang, Wei-Cheng and Lu, Shueh-Chou and Huang, Chun-Rong and Chung, Pau-Choo and Lai, Yun-Yang",
          journal = "IEEE Transactions on Intelligent Transportation Systems",
          number = "1",
          pages = "346--361",
          publisher = "IEEE",
          title = "Driver monitoring using sparse representation with part-based temporal face descriptors",
          volume = "21",
          year = "2019"
      }
      
    Wang et al., Real-Time Workload Classification during Driving using HyperNetworks, IROS, 2018 | paper
      Dataset(s): private
      @inproceedings{2018_IROS_Wang,
          author = "Wang, Ruohan and Amadori, Pierluigi V and Demiris, Yiannis",
          booktitle = "IROS",
          title = "Real-time workload classification during driving using hypernetworks",
          year = "2018"
      }
      
    Abouelnaga et al., Real-time Distracted Driver Posture Classification, NeurIPSW, 2018 | paper
      Dataset(s): AUCDD
      @inproceedings{2017_NeurIPS_Abouelnaga,
          author = "Abouelnaga, Yehya and Eraqi, Hesham M. and Moustafa, Mohamed N.",
          booktitle = "NeurIPS Workshop on Machine Learning for Intelligent Transportation Systems",
          title = "eal-time Distracted Driver Posture Classification",
          year = "2017"
      }
      
    Munoz et al., Distinguishing patterns in drivers’ visual attention allocation using Hidden Markov Models, Transportation Research Part F, 2016 | paper
      Dataset(s): private
      @article{2016_TransRes_Munoz,
          author = "Mu{\\textasciitilde n}oz, Mauricio and Reimer, Bryan and Lee, Joonbum and Mehler, Bruce and Fridman, Lex",
          journal = "Transportation Research Part F: Traffic Psychology and Behaviour",
          pages = "90--103",
          title = "Distinguishing patterns in drivers’ visual attention allocation using Hidden Markov Models",
          volume = "43",
          year = "2016"
      }
      
    Liao et al., Detection of Driver Cognitive Distraction: A Comparison Study of Stop-Controlled Intersection and Speed-Limited Highway, Trans. ITS, 2016 | paper
      Dataset(s): private
      @article{2016_T-ITS_Liao,
          author = "Liao, Yuan and Li, Shengbo Eben and Wang, Wenjun and Wang, Ying and Li, Guofa and Cheng, Bo",
          journal = "IEEE Transactions on Intelligent Transportation Systems",
          number = "6",
          pages = "1628--1637",
          publisher = "IEEE",
          title = "Detection of driver cognitive distraction: A comparison study of stop-controlled intersection and speed-limited highway",
          volume = "17",
          year = "2016"
      }
      
    Li et al., Detecting Drivers’ Mirror-Checking Actions and Its Application to Maneuver and Secondary Task Recognition, Trans. ITS, 2016 | paper
      Dataset(s): private
      @article{2016_T-ITS_Li,
          author = "Li, Nanxiang and Busso, Carlos",
          journal = "IEEE Transactions on Intelligent Transportation Systems",
          number = "4",
          pages = "980--992",
          publisher = "IEEE",
          title = "Detecting drivers' mirror-checking actions and its application to maneuver and secondary task recognition",
          volume = "17",
          year = "2015"
      }
      
    Liao et al., Detection of Driver Cognitive Distraction: A Comparison Study of Stop-Controlled Intersection and Speed-Limited Highway, IV, 2016 | paper
      Dataset(s): private
      @inproceedings{2016_IV_Liao,
          author = "Liao, Yuan and Li, Shengbo Eben and Li, Guofa and Wang, Wenjun and Cheng, Bo and Chen, Fang",
          booktitle = "IV",
          title = "Detection of driver cognitive distraction: An SVM based real-time algorithm and its comparison study in typical driving scenarios",
          year = "2016"
      }
      
    Kim et al., Fusion of Driver-information Based Driver Status Recognition for Co-Pilot System, IV, 2016 | paper
      Dataset(s): private
      @inproceedings{2016_IV_Kim,
          author = "Kim, Jinwoo and Kim, Kitae and Yoon, Daesub and Koo, Yongbon and Han, Wooyong",
          booktitle = "2016 Ieee Intelligent Vehicles Symposium (iv)",
          organization = "IEEE",
          pages = "1398--1403",
          title = "Fusion of driver-information based driver status recognition for co-pilot system",
          year = "2016"
      }
      
    Liu et al., Driver Distraction Detection Using Semi-Supervised Machine Learning, Trans. ITS, 2015 | paper
      Dataset(s): private
      @article{2015_T-ITS_Liu,
          author = "Liu, Tianchi and Yang, Yan and Huang, Guang-Bin and Yeo, Yong Kiang and Lin, Zhiping",
          journal = "IEEE Transactions on Intelligent Transportation Systems",
          number = "4",
          pages = "1108--1120",
          title = "Driver distraction detection using semi-supervised machine learning",
          volume = "17",
          year = "2015"
      }
      
    Li et al., Predicting Perceived Visual and Cognitive Distractions of Drivers With Multimodal Features, Trans. ITS, 2015 | paper
      Dataset(s): private
      @article{2015_T-ITS_Li,
          author = "Li, Nanxiang and Busso, Carlos",
          journal = "IEEE Transactions on Intelligent Transportation Systems",
          number = "1",
          pages = "51--65",
          title = "Predicting perceived visual and cognitive distractions of drivers with multimodal features",
          volume = "16",
          year = "2014"
      }
      
    Braunagel et al., Driver-Activity Recognition in the Context of Conditionally Autonomous Driving, Trans. ITS, 2015 | paper
      Dataset(s): private
      @inproceedings{2015_T-ITS_Braunagel,
          author = "Braunagel, Christian and Kasneci, Enkelejda and Stolzmann, Wolfgang and Rosenstiel, Wolfgang",
          booktitle = "ITSC",
          title = "Driver-activity recognition in the context of conditionally autonomous driving",
          year = "2015"
      }
      
    Liu et al., Cluster regularized extreme learning machine for detecting mixed-type distraction in driving, ITSC, 2015 | paper
      Dataset(s): private
      @inproceedings{2015_ITSC_Liu,
          author = "Liu, Tianchi and Yang, Yan and Huang, Guang-Bin and Lin, Zhiping and Klanner, Felix and Denk, Cornelia and Rasshofer, Ralph H",
          booktitle = "ITSC",
          title = "Cluster regularized extreme learning machine for detecting mixed-type distraction in driving",
          year = "2015"
      }
      
    Seshadri et al., Driver Cell Phone Usage Detection on Strategic Highway Research Program (SHRP2) Face View Videos, CVPRW, 2015 | paper
      Dataset(s): SHRP2
      @inproceedings{2015_CVPRW_Seshadri,
          author = "Seshadri, Keshav and Juefei-Xu, Felix and Pal, Dipan K and Savvides, Marios and Thor, Craig P",
          booktitle = "CVPRW",
          title = "Driver cell phone usage detection on strategic highway research program (shrp2) face view videos",
          year = "2015"
      }
      
    Hirayama et al., Analysis of Peripheral Vehicular Behavior in Driver’s Gaze Transition: Differences between Driver’s Neutral and Cognitive Distraction States, ITSC, 2014 | paper
      Dataset(s): private
      @inproceedings{2014_ITSC_Hirayama,
          author = "Hirayama, Takatsugu and Sato, Shota and Mase, Kenji and Miyajima, Chiyomi and Takeda, Kazuya",
          booktitle = "ITSC",
          title = "Analysis of peripheral vehicular behavior in driver's gaze transition: Differences between driver's neutral and cognitive distraction states",
          year = "2014"
      }
      
    Tango et al., Real-Time Detection System of Driver Distraction Using Machine Learning, Trans. ITS, 2013 | paper
      Dataset(s): private
      @article{2013_T-ITS_Tango,
          author = "Tango, Fabio and Botta, Marco",
          journal = "IEEE Transactions on Intelligent Transportation Systems",
          number = "2",
          pages = "894--905",
          title = "Real-time detection system of driver distraction using machine learning",
          volume = "14",
          year = "2013"
      }
      
    Mbouna et al., Visual Analysis of Eye State and Head Pose for Driver Alertness Monitoring, Trans. ITS, 2013 | paper
      @article{2013_T-ITS_Mbouna,
          author = "Mbouna, Ralph Oyini and Kong, Seong G and Chun, Myung-Geun",
          journal = "IEEE Transactions on Intelligent Transportation Systems",
          number = "3",
          pages = "1462--1469",
          title = "Visual analysis of eye state and head pose for driver alertness monitoring",
          volume = "14",
          year = "2013"
      }
      
    Masala et al., Detecting Driver Inattention by Rough Iconic Classification, IV, 2013 | paper
      Dataset(s): private
      @inproceedings{2013_IV_Masala,
          author = "Masala, Giovanni Luca and Grosso, Enrico",
          booktitle = "2013 IEEE Intelligent Vehicles Symposium (IV)",
          organization = "IEEE",
          pages = "913--918",
          title = "Detecting driver inattention by rough iconic classification",
          year = "2013"
      }
      
    Ahlstrom et al., A Gaze-Based Driver Distraction Warning System and Its Effect on Visual Behavior, Driver Distraction and Inattention, 2013 | paper
      Dataset(s): private
      @inbook{2013_DDI_Ahlstrom,
          author = "Kircher, Katja and Ahlstrom, Christer",
          editor = "Regan, Michael and Victor, Trent and Lee, John",
          chapter = "The Driver Distraction Detection Algorithm AttenD",
          pages = "327-348",
          publisher = "Ashgate Publishing Ltd.",
          title = "Driver Distraction and Inattention: Advances in Research and Countermeasures, Volume 1",
          year = "2013"
      }
      
    Hirayama et al., Detection of Driver Distraction based on Temporal Relationship between Eye-Gaze and Peripheral Vehicle Behavior, ITSC, 2012 | paper
      Dataset(s): private
      @inproceedings{2012_ITSC_Hirayama,
          author = "Hirayama, Takatsugu and Mase, Kenji and Takeda, Kazuya",
          booktitle = "ITSC",
          title = "Detection of driver distraction based on temporal relationship between eye-gaze and peripheral vehicle behavior",
          year = "2012"
      }
      
    Wollmer et al., Online Driver Distraction Detection UsingLong Short-Term Memory, Trans. ITS, 2011 | paper
      Dataset(s): private
      @article{2011_T-ITS_Wollmer,
          author = {Wollmer, Martin and Blaschke, Christoph and Schindl, Thomas and Schuller, Bj{\"o}rn and Farber, Berthold and Mayer, Stefan and Trefflich, Benjamin},
          journal = "IEEE Transactions on Intelligent Transportation Systems",
          number = "2",
          pages = "574--582",
          title = "Online driver distraction detection using long short-term memory",
          volume = "12",
          year = "2011"
      }
      
    Jo et al., Vision-based method for detecting driver drowsiness and distraction in driver monitoring system, Optical Engineering, 2011 | paper
      Dataset(s): private
      @article{2011_OptEng_Jo,
          author = "Jo, Jaeik and Lee, Sung Joo and Kim, Jaihie and Jung, Ho Gi and Park, Kang Ryoung",
          journal = "Optical Engineering",
          number = "12",
          pages = "127202",
          title = "Vision-based method for detecting driver drowsiness and distraction in driver monitoring system",
          volume = "50",
          year = "2011"
      }
      
    Flores et al., Driver drowsiness detection system under infrared illumination for an intelligent vehicle, IET Intelligent Transport Systems, 2011 | paper
      Dataset(s): private
      @article{2011_IET_Flores,
          author = "Flores, Marco Javier and Armingol, J Ma and de la Escalera, Arturo",
          journal = "IET Intelligent Transport Systems",
          number = "4",
          pages = "241--251",
          publisher = "IET",
          title = "Driver drowsiness detection system under infrared illumination for an intelligent vehicle",
          volume = "5",
          year = "2011"
      }