Abstract: A computer-implemented method for annotating driving scenario sensor data, including the steps of receiving raw sensor data, the raw sensor data comprising a plurality of successive LIDAR point clouds and/or a plurality of successive camera images, recognizing objects in each image of the camera data and/or each point cloud using one or more neural networks, correlating objects within successive images and/or point clouds, removing false positive results on the basis of plausibility criteria, and exporting the annotated sensor data of the driving scenario.

Abstract: A computer-implemented method for generating a bird’s eye view image of a scene includes: (a) acquiring at least one lidar frame comprising points with inherent distance information and at least one camera image of the scene; (b) generating a mesh representation of the scene by using the at least one lidar frame, the mesh representation representing surfaces shown in the scene with inherent distance information; (c) generating a mask image by classifying pixels of the at least one camera image as representing ground pixels or non-ground pixels of the at least one camera image; and (d) generating the bird’s eye view image by enhanced inverse perspective mapping exploiting distance information inherent to the surfaces of the mesh representation, pixels of the mask image classified as ground pixels, and the at least one camera image.