Detecting Phone-Induced Pedestrian Distraction via a Multimodal Fusion Transformer
The increasing reliance on mobile phones has made phone-induced pedestrian distraction increasingly prevalent. Activities such as texting, watching videos, and making phone calls have become significant contributors to traffic accidents. Reliable detection of pedestrian distraction is essential for autonomous vehicles, as it improves situational awareness and enables timely risk assessment, thereby supporting safe motion planning and vehicle control. We propose a multimodal fusion Transformer (MFT) for detecting phone-induced pedestrian distraction. MFT jointly extracts skeletal dynamics from body pose keypoints and visual appearance features from pedestrian images, effectively leveraging...
| Authors | Yuanzhe Li, Hounian Liu, Xiaotong Chang et al. |
|---|---|
| Primary category | cs.CV |
| Published | 20 September 2026 |
| Last updated at source | 20 September 2026 |
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