Low-Latency Embedded Driver Monitoring System with a Multi-Task Neural Network
Road traffic accidents remain a significant global concern, with the majority attributed to human factors such as driver distraction and fatigue. This study proposes a camera-based approach to derive useful indicators to assess driver attentiveness and alertness. The proposed pipeline jointly satisfies the stringent real-time requirements imposed by the critical application and minimizes the computational requirements to allow for deployment on a tight computational budget. To this end, we develop a lightweight multi-task neural network that predicts multiple indicators for the face region in a single forward pass. The developed model is integrated into a complete execution workflow to pr...
| Authors | Carmelo Scribano, Giovanni Cappelletti, Elia Giacobazzi et al. |
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| Primary category | cs.CV |
| Published | 4 May 2026 |
| Last updated at source | 4 May 2026 |
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