Report
DMD: A Large-Scale Multi-Modal Driver Monitoring Dataset for Attention and Alertness Analysis
| العنوان: | DMD: A Large-Scale Multi-Modal Driver Monitoring Dataset for Attention and Alertness Analysis |
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| المؤلفون: | Ortega, Juan Diego, Kose, Neslihan, Cañas, Paola, Chao, Min-An, Unnervik, Alexander, Nieto, Marcos, Otaegui, Oihana, Salgado, Luis |
| سنة النشر: | 2020 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing |
| الوصف: | Vision is the richest and most cost-effective technology for Driver Monitoring Systems (DMS), especially after the recent success of Deep Learning (DL) methods. The lack of sufficiently large and comprehensive datasets is currently a bottleneck for the progress of DMS development, crucial for the transition of automated driving from SAE Level-2 to SAE Level-3. In this paper, we introduce the Driver Monitoring Dataset (DMD), an extensive dataset which includes real and simulated driving scenarios: distraction, gaze allocation, drowsiness, hands-wheel interaction and context data, in 41 hours of RGB, depth and IR videos from 3 cameras capturing face, body and hands of 37 drivers. A comparison with existing similar datasets is included, which shows the DMD is more extensive, diverse, and multi-purpose. The usage of the DMD is illustrated by extracting a subset of it, the dBehaviourMD dataset, containing 13 distraction activities, prepared to be used in DL training processes. Furthermore, we propose a robust and real-time driver behaviour recognition system targeting a real-world application that can run on cost-efficient CPU-only platforms, based on the dBehaviourMD. Its performance is evaluated with different types of fusion strategies, which all reach enhanced accuracy still providing real-time response. Comment: Accepted to ECCV 2020 workshop - Assistive Computer Vision and Robotics |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1007/978-3-030-66823-5_23 |
| URL الوصول: | http://arxiv.org/abs/2008.12085 |
| رقم الانضمام: | edsarx.2008.12085 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.1007/978-3-030-66823-5_23 |
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