Abstract: A method for a sensor-based and memory-based representation of a surroundings of a vehicle. The vehicle includes an imaging sensor for detecting the surroundings. The method includes: detecting a sequence of images; determining distance data on the basis of the detected images and/or of a distance sensor of the vehicle, the distance data comprising distances between the vehicle and objects in the surroundings of the vehicle; generating a three-dimensional structure of a surroundings model on the basis of the distance data; recognizing at least one object in the surroundings of the vehicle on the basis of the detected images, in particular by a neural network; loading a synthetic object model on the basis of the recognized object; adapting the generated three-dimensional structure of the surroundings model on the basis of the synthetic object model and on the basis of the distance data; and displaying the adapted surroundings model.

Abstract: Method for generating an encoded image 1, wherein a camera system provides a camera image 2, wherein the camera image 2 comprises anonymous image sections 3 without personal data and sensitive image sections 4 containing personal data, wherein the camera image 2 is analyzed based on an image recognition algorithm to detect the sensitive image sections 4, wherein an encoded image 1 is generated, wherein in order to generate the encoded image 1 the sensitive image sections 4 of the camera image 2 are anonymized and image contents of the sensitive image sections 4 of the camera image are stored in the encoded image 1 in cryptographically encoded form.

Abstract: A method, including recording a first and a second camera image; the first camera image and the second camera image having an overlap region. The method includes: assigning pixels of the first camera image and pixels of the second camera image to predefined points of a three-dimensional lattice structure, the predefined points being situated in a region of the three-dimensional lattice structure, which represents the overlap region; ascertaining a color information item difference for each predefined point as a function of the assigned color information items; ascertaining a quality value as a function of the ascertained color information item difference at the specific, predefined point; determining a global color transformation matrix as a function of the color information item differences, weighted as a function of the corresponding quality value; and adapting the second camera image as a function of the determined color transformation matrix.

Abstract: A method for enriching a target image, which a target camera system had recorded of a scene, with additional information, with which at least one source image that a source camera system had recorded of the same scene from a different perspective, has already been enriched. The method includes: assigning 3D locations in the three-dimensional space, which correspond to the positions of the source pixels in the source image, to source pixels of the source image; assigning additional information which is assigned to source pixels, to the respective, associated 3D locations; assigning those target pixels of the target image, whose positions in the target image correspond to the 3D locations, to the 3D locations; assigning additional information, which is assigned to 3D locations, to associated target pixels. A method for training a Kl module is also described.

Abstract: A method for a sensor-based and memory-based representation of a surroundings of a vehicle. The vehicle includes an imaging sensor for detecting the surroundings. The method includes: detecting a sequence of images; determining distance data on the basis of the detected images and/or of a distance sensor of the vehicle, the distance data comprising distances between the vehicle and objects in the surroundings of the vehicle; generating a three-dimensional structure of a surroundings model on the basis of the distance data; recognizing at least one object in the surroundings of the vehicle on the basis of the detected images, in particular by a neural network; loading a synthetic object model on the basis of the recognized object; adapting the generated three-dimensional structure of the surroundings model on the basis of the synthetic object model and on the basis of the distance data; and displaying the adapted surroundings model.

Abstract: A method, including recording a first and a second camera image; the first camera image and the second camera image having an overlap region. The method includes: assigning pixels of the first camera image and pixels of the second camera image to predefined points of a three-dimensional lattice structure, the predefined points being situated in a region of the three-dimensional lattice structure, which represents the overlap region; ascertaining a color information item difference for each predefined point as a function of the assigned color information items; ascertaining a quality value as a function of the ascertained color information item difference at the specific, predefined point; determining a global color transformation matrix as a function of the color information item differences, weighted as a function of the corresponding quality value; and adapting the second camera image as a function of the determined color transformation matrix.