Improving Computer Vision by Virtual Optimization of Matrix Headlights Using Surface Properties
Nathalie Müller, Mirko Waldner, Torsten Bertram · 2024
The contribution at hand presents a novel method for optimizing the illumination of matrix headlights in simulation to improve the environment perception of camera-based computer vision and the object detection quality for automated driving. With high-definition (HD) matrix headlights in combination with the developed novel algorithm, different surfaces and materials in the environment can be illuminated with different intensities, resulting in material-based and -optimized illumination that is individually adapted to each material. This environment-optimal illumination improves the detection quality of computer vision, which is better than conventional homogenous headlamp illumination. Additionally, it is possible to achieve a similar detection quality using the novel proposed optimization approach with potential energy savings of up to 88%.