Computer-implemented method and system for creating a virtual environment for a vehicle
AssigneedSPACE GmbH
InventorsLeon BOHNMANN, Frederik VIEZENS
Life of this patent
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Abstract
A computer-implemented method and system for generating a virtual environment for a vehicle for testing highly automated driving functions of a motor vehicle. The method comprises projecting the pixel-based classified camera image data onto the pre-acquired LiDAR point cloud data, wherein each point of the LiDAR point cloud, superimposed by classified pixels of the camera image data, in particular having the same image coordinates, is assigned an identical class and an instance segmentation of the classified LiDAR point cloud data for determining at least one real object comprised by a class. A computer program and a computer-readable data carrier are also provided.
Claims15
A computer-implemented method for creating a virtual vehicle environment for testing highly automated driving functions of a motor vehicle, the method comprising:
- providing pre-acquired camera image data and LiDAR point cloud data of a real vehicle environment;
- performing pixel-based classification of the pre-acquired camera image data using a machine learning algorithm, which outputs an associated class and a confidence value corresponding to the classification for each pixel;
- projecting the pixel-based classified camera image data onto the pre-acquired LiDAR point cloud data, wherein each point of the LiDAR point cloud, superimposed by classified pixels of the camera image data or points having the same image coordinates, is assigned an identical class;
- instance segmenting the classified LiDAR point cloud data to determine at least one real object comprised by a class;
- selecting and calling a stored, synthetically generated first object corresponding to the at least one real object or procedural generation of a synthetically generated second object corresponding to the at least one real object;
- and
- integrating the synthetically generated first object or the synthetically generated second object into a specified virtual vehicle environment.
A system to generate a virtual vehicle environment for testing highly automated driving functions of a motor vehicle using pre-acquired video image data, radar data and/or a LiDAR point cloud of a real vehicle environment, the system comprising:
- a data memory to provide pre-acquired camera image data and LiDAR point cloud data of a real vehicle environment;
- a calculation device for pixel-based classification of the pre-acquired camera image data using a machine learning algorithm which is configured to output for each pixel an associated class and a confidence value corresponding to the classification,
- wherein the calculation device is configured to project the pixel-based classified camera image data onto the pre-acquired LiDAR point cloud data and to assign an identical class to respective points of the LiDAR point cloud, each superimposed by classified pixels of the camera image data, in particular having the same image coordinates,
- wherein the calculation device is configured to perform an instance segmentation of the classified LiDAR point cloud data to determine at least one real object comprised by a class,
- wherein the calculation device is configured to select and call a stored, synthetically generated first object or a procedural generation of a synthetically generated second object corresponding to the at least one real object, and
- wherein the calculation device is configured to integrate the synthetically generated first or second object into a specified virtual vehicle environment.
Dependencies are inferred from the claim text.