Abstract:

This study proposes an advanced nighttime pedestrian detection framework integrating infrared vision and millimeter-wave (MMW) radar to enhance detection accuracy and reliability in low-light traffic environments. The improved YOLOv5 model extracts precise localization and category-specific features from infrared images, ensuring accurate and efficient object recognition. MMW radar captures essential distance and velocity data for precise motion tracking and target identification.

Description:

.