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 and a device for improved training of a classifier. For this purpose, the device for detecting an object has a first image recording device, which is situated in a first position for recording the object from a first perspective. The device furthermore has a stored first classifier, which is configured to detect the object based on the recorded first perspective. At least one second image recording device is situated in a second position for recording the object from a second perspective, which differs from the first perspective. Furthermore, a data processing device is configured to detect the object recorded by the first image recording device based on the first classifier and to assign to the second perspective a class predetermined by the first classifier. This makes it possible to expand the existing classifier to include the detection of the object from different additional perspectives.

Abstract: A method for classifying an object for a vehicle. The method includes at least: classifying, extracting and creating. In the classifying, an object from a camera image is classified using a generic classifier. In the extracting, at least one specific object feature assigned to the object is extracted from the camera image. In the creating, a specific classifier is created using the specific object feature.

Abstract: A method for detecting objects in the surroundings of a vehicle. The method includes reading in a first image, of a vehicle camera, which represents the surroundings taken using a first exposure time and reading in a second image of the vehicle camera, which was taken after the first image and using a second exposure time, the second exposure time differing from the first exposure time, and extracting an image detail from the second image, the image detail representing a smaller area of the surroundings than the first image. During the extracting, a position of the image detail in the second image is determined based on at least one parameter which represents information on travel of the vehicle and/or a position of an infrastructure measure in front of the vehicle and/or which is independent of a moving object that was detected in a preceding step in the image detail.

Abstract: A method and a device for improved training of a classifier. For this purpose, the device for detecting an object has a first image recording device, which is situated in a first position for recording the object from a first perspective. The device furthermore has a stored first classifier, which is configured to detect the object based on the recorded first perspective. At least one second image recording device is situated in a second position for recording the object from a second perspective, which differs from the first perspective. Furthermore, a data processing device is configured to detect the object recorded by the first image recording device based on the first classifier and to assign to the second perspective a class predetermined by the first classifier. This makes it possible to expand the existing classifier to include the detection of the object from different additional perspectives.

Abstract: A method for classifying an object for a vehicle. The method includes at least: classifying, extracting and creating. In the classifying, an object from a camera image is classified using a generic classifier. In the extracting, at least one specific object feature assigned to the object is extracted from the camera image. In the creating, a specific classifier is created using the specific object feature.

Abstract: A method for recognizing a weather condition in the surroundings of a vehicle. The method includes a step of ascertaining at least one imaging feature in image information. The image information represents a depiction of at least a portion of the surroundings, and the imaging feature represents a light effect on a reflective or luminescent object in the portion of the surroundings. In addition, the method includes a step of determining weather information for characterizing the weather condition based on a comparison between the imaging feature and at least one expected value.

Abstract: A method for providing a signal to a light control unit of at least one headlight of a vehicle that has a camera for acquiring a surrounding environment of a vehicle, the method including a step of determination of an interval between the vehicle and another vehicle using the camera. The method further includes a step of determination of a distance between the vehicle and the other vehicle using a camera-independent sensor. In addition, the method includes a step of plausibilization of the interval using the distance, the interval being plausibilized if a difference between the interval and the distance is smaller than a tolerance value. Finally, the method includes a step of provision the interval via an interface to a light control unit of the headlight.

Abstract: A method for analyzing an image recorded by a camera of a vehicle. The method includes a step of reading the image of the camera. Furthermore, the method includes a step of recognizing at least one object in a subsection of the image, the subsection imaging a smaller area of the vehicle surroundings than the image. Furthermore, the method includes a step of transmitting the subsection and/or information about the subsection of the image to a driver assistance module. Finally, the method includes a step of using the subsection of the image and/or the information about the subsection of the image instead of the entire image in the driver assistance module, in order to analyze the image recorded by the camera.

Abstract: A method for influencing a lighting scene ahead of a vehicle is described, the method including a step of reading in information regarding a position of at least one recognized object and regarding a class of the recognized object. Furthermore, the method includes a step of assigning a lighting area, related to the position of the object, having a lighting intensity related to the class of the object for the lighting area. The method also includes a step of adapting the lighting scene, taking into account the lighting area and the associated lighting intensity.

Abstract: A method for estimating a roadway course in a roadway section ahead of a vehicle in the direction of travel is provided. The method includes recognizing at least one reflective or self-luminous object in an image of the roadway section. The method also includes ascertaining a position of the at least one object based on the image of the roadway section. The method also includes estimating the roadway course using the ascertained position of the at least one object.

Abstract: A method for classifying a light object located ahead of a vehicle, the method including a determination of a brightness curve assigned to the light object via at least two images which depict the light object at different times and a combination of the brightness curve with a characteristic brightness curve, in order to classify the light object.

Abstract: A method for estimating a roadway course in a roadway section ahead of a vehicle in the direction of travel is provided. The method includes recognizing at least one reflective or self-luminous object in an image of the roadway section. The method also includes ascertaining a position of the at least one object based on the image of the roadway section. The method also includes estimating the roadway course using the ascertained position of the at least one object.

Abstract: A method for recognizing a weather condition in the surroundings of a vehicle. The method includes a step of ascertaining at least one imaging feature in image information. The image information represents a depiction of at least a portion of the surroundings, and the imaging feature represents a light effect on a reflective or luminescent object in the portion of the surroundings. In addition, the method includes a step of determining weather information for characterizing the weather condition based on a comparison between the imaging feature and at least one expected value.

Abstract: A method for analyzing an image recorded by a camera of a vehicle. The method includes a step of reading the image of the camera. Furthermore, the method includes a step of recognizing at least one object in a subsection of the image, the subsection imaging a smaller area of the vehicle surroundings than the image. Furthermore, the method includes a step of transmitting the subsection and/or information about the subsection of the image to a driver assistance module. Finally, the method includes a step of using the subsection of the image and/or the information about the subsection of the image instead of the entire image in the driver assistance module, in order to analyze the image recorded by the camera.

Abstract: A method for detecting objects in the surroundings of a vehicle. The method includes reading in a first image, of a vehicle camera, which represents the surroundings taken using a first exposure time and reading in a second image of the vehicle camera, which was taken after the first image and using a second exposure time, the second exposure time differing from the first exposure time, and extracting an image detail from the second image, the image detail representing a smaller area of the surroundings than the first image. During the extracting, a position of the image detail in the second image is determined based on at least one parameter which represents information on travel of the vehicle and/or a position of an infrastructure measure in front of the vehicle and/or which is independent of a moving object that was detected in a preceding step in the image detail.

Abstract: A method for influencing a lighting scene ahead of a vehicle is described, the method including a step of reading in information regarding a position of at least one recognized object and regarding a class of the recognized object. Furthermore, the method includes a step of assigning a lighting area, related to the position of the object, having a lighting intensity related to the class of the object for the lighting area. The method also includes a step of adapting the lighting scene, taking into account the lighting area and the associated lighting intensity.

Abstract: A method for classifying a light object located ahead of a vehicle, the method including a determination of a brightness curve assigned to the light object via at least two images which depict the light object at different times and a combination of the brightness curve with a characteristic brightness curve, in order to classify the light object.