Lukas Stäcker

"Radar-Camera Fusion for automotive environment perception"

To overcome the limitations of single sensor setups, current research aims at leveraging the strengths of a diverse sensor combination. In the automotive industry, radar-camera fusion is a particularly interesting sensor combination due to its moderate cost, complementary environmental information and possibility for seamless sensor integration. In particular, radar sensors provide accurate and direct measurements of the distance and radial relative velocity, while cameras provide accurate azimuth and elevation measurements as well as rich semantic context information. However, it remains a challenge to determine how to optimally fuse these heterogeneous data sources. In my work, I research different methods of radar-camera fusion within deep neural networks to optimize object detection performance.

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