mlsanityData to 7 Oct 2026

Real-Time Driver Monitoring Systems through Modality and View Analysis

arXiv 2210.09441 ↗First posted 17 Oct 2022cs.CV cs.HC cs.ROcited by 5

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Abstract (arXiv)

Driver distractions are known to be the dominant cause of road accidents. While monitoring systems can detect non-driving-related activities and facilitate reducing the risks, they must be accurate and efficient to be applicable. Unfortunately, state-of-the-art methods prioritize accuracy while ignoring latency because they leverage cross-view and multimodal videos in which consecutive frames are highly similar. Thus, in this paper, we pursue time-effective detection models by neglecting the temporal relation between video frames and investigate the importance of each sensing modality in detecting drives' activities. Experiments demonstrate that 1) our proposed algorithms are real-time and can achieve similar performances (97.5% AUC-PR) with significantly reduced computation compared with video-based models; 2) the top view with the infrared channel is more informative than any other single modality. Furthermore, we enhance the DAD dataset by manually annotating its test set to enable multiclassification. We also thoroughly analyze the influence of visual sensor types and their placements on the prediction of each class. The code and the new labels will be released.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 23 of its 35 references that are in the map. First posted on arXiv 17 Oct 2022.

Builds on

23 of 35 references.

References · 23

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11 more
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Cited by year

Citing papers per year: 2023: 1; 2024: 2; 2025: 2.

5 papers.

  1. 2023AIDE: A Vision-Driven Multi-View, Multi-Modal, Multi-Tasking Dataset for Assistive Driving Perceptioncited by 39
  2. 2024Multi-modality action recognition based on dual feature shift in vehicle cabin monitoringcited by 8
  3. 2024MultiFuser: Multimodal Fusion Transformer for Enhanced Driver Action Recognitioncited by 4
  4. 2025Cross-Asset Risk Management: Integrating LLMs for Real-Time Monitoring of Equity, Fixed Income, and Currency Marketscited by 2
  5. 2025Spatial-Temporal Perception with Causal Inference for Naturalistic Driving Action Recognitioncited by 0