Publikation
Cross-Dataset Experimental Study of Radar-Camera Fusion in Bird's-Eye View
Lukas Stephan Stäcker; Philipp Heidenreich; Jason Raphael Rambach; Didier Stricker
In: IEEE (Hrsg.). Proceedings of the 31st European Signal Processing Conference. European Signal Processing Conference (EUSIPCO-2023), 31st, September 4-8, Helsinki, Finland, IEEE, 2023.
Zusammenfassung
By exploiting complementary sensor information,
radar and camera fusion systems have the potential to provide a
highly robust and reliable perception system for advanced driver
assistance systems and automated driving functions. Recent
advances in camera-based object detection offer new radar-camera
fusion possibilities with bird’s eye view feature maps.
In this work, we propose a novel and flexible fusion network
and evaluate its performance on two datasets: nuScenes and
View-of-Delft. Our experiments reveal that while the camera
branch needs large and diverse training data, the radar branch
benefits more from a high-performance radar. Using transfer
learning, we improve the camera’s performance on the smaller
dataset. Our results further demonstrate that the radar-camera
fusion approach significantly outperforms the camera-only and
radar-only baselines.