Abstract: A system for translation of images between two distinct heterogenous cameras and a method thereof is disclosed. The system includes a source camera, a target camera, two generative adversarial networks, a transformation prediction module and at least a warping module. The transformation prediction module is configured using the system and method to derive a transformation parameter. The transformation prediction module is optimized using a loss function comprising loss between a translated source image vis-à-vis a target image and a translated target image vis-à-vis a source image.

Abstract: A method for recognizing an object includes reading in a first image signal that represents a first camera image recorded by a mono camera, and a second image signal that represents a second camera image recorded by the mono camera. First pixels situated on an image line of the first camera image are selected from the first image signal. Second pixels are identified from the second image signal, the second pixels corresponding to the first pixels. A flux signal is formed using the first pixels and the second pixels, the flux signal representing an optical flux profile for the first pixels situated along the image line. The flux profile represented by the flux signal is segmented into a plurality of segments, each of which represents a plane in the vehicle surroundings. An object signal that represents a recognized object is determined, using the plurality of segments.

Abstract: A method for processing sensor data in a system that includes multiple sensors for detecting at least a subarea of surroundings around the system. The method includes at least the following steps: a) reading in sensor data detected at least partially in parallel, b) checking whether an at least partial impairment of the detection by the respective sensor may be established for one or for multiple of the sensors on the basis of the read-in sensor data, c) adapting the use of the sensor data, taking the check from step b) into account.

Abstract: A method for recognizing an object includes reading in a first image signal that represents a first camera image recorded by a mono camera, and a second image signal that represents a second camera image recorded by the mono camera. First pixels situated on an image line of the first camera image are selected from the first image signal. Second pixels are identified from the second image signal, the second pixels corresponding to the first pixels. A flux signal is formed using the first pixels and the second pixels, the flux signal representing an optical flux profile for the first pixels situated along the image line. The flux profile represented by the flux signal is segmented into a plurality of segments, each of which represents a plane in the vehicle surroundings. An object signal that represents a recognized object is determined, using the plurality of segments.

Abstract: A method of determining calibration parameters of a camera comprises taking a first image of an object, taking a second image of the object, wherein the position of the camera with respect to the object is changed between the first and the second image, the calibration parameters of the camera being fixed between the first and the second image, determining a transformation that is adapted to transform a portion of the first into a corresponding portion of the second image, and determining the calibration parameters from the transformation.

Abstract: A method of determining calibration parameters of a camera comprises taking a first image of an object, taking a second image of the object, wherein the position of the camera with respect to the object is changed between the first and the second image, the calibration parameters of the camera being fixed between the first and the second image, determining a transformation that is adapted to transform a portion of the first into a corresponding portion of the second image, and determining the calibration parameters from the transformation.