Abstract: A method for determining a motion model of an object by an assistance system is disclosed. The method involves capturing an image of the surroundings with the moving object by a capturing device, encoding the image by a feature extraction module of a neural network of an electronic computing device, decoding the encoded image by an object segmentation module and generating a first loss function, decoding the at least one encoded image by a bounding box estimation module and generating a second loss function, decoding the second loss function depending on the decoding of the image by a motion decoding module and generating a third loss function; and determining the motion model depending on the first loss function and the third loss function.

Abstract: A method for forming a point cloud corresponding to the topography of an imaged environment involves acquiring an image of the environment with a camera having a WFOV lens mounted on a vehicle; changing the camera pose by an adjustment greater than a threshold; and acquiring another image of the environment with the camera at the changed pose. The images are mapped onto respective surfaces to form respective mapped images, defined by the same nonplanar geometry. One of the mapped images is divided into blocks of pixels. For each block, a depth map is formed by performing a search through the other mapped image to evaluate a disparity in the position of the location of the block of pixels in each of the mapped images. The depth map is converted into a partial point cloud corresponding to the local topography of the environment surrounding the vehicle as it moves through the environment.

Abstract: A method for determining a state of a tailgate (9) of a pickup vehicle (1) by a camera system (2), includes capturing a cargo bed (5) of the pickup vehicle (1) in an image (8) captured by a camera (3), determining a first region of interest (ROI1) in the captured image (8) by an electronic computing device (4) of the camera system (2), wherein the first region of interest (ROI1) includes the potential tailgate (9) at least partially, determining a parameter optically characterizing the tailgate (9) depending on the captured image (8), analyzing the first region of interest (ROI1) with regard to the characterizing parameter, and determining a closed state of the tailgate (9) as state or determining an opened state of the tailgate (9) as state depending on the analysis of the first region of interest (ROI1). A computer program product, an electronic computing device (4) as well as a camera system (2) are also disclosed.

Abstract: A method for determining a camera parameter for a camera (3) of a camera system (2) of a pickup vehicle (1) includes capturing a cargo bed (5) of the pickup vehicle (1) in an image (18) captured by using the camera (3), determining at least one first cargo bed edge line of the cargo bed (5) by optical analysis of the captured image (18) by using an electronic computing device (4) of the camera system (3), providing a function parameter for a cost function (15) by analysis of at least one first cargo bed edge line by using a regression-analysis algorithm of a solver module (14) of the electronic computing device (4), and determining the camera parameter on the basis of the cost function (15) depending on the provided function parameter by using the electronic computing device (4). A computer program product, an electronic computing device (4) as well as a camera system (2) are also disclosed.

Abstract: The invention relates to a method for capturing an object (9) in an environmental region (8) of a motor vehicle (1) based on a sequence of images (10, 11) of the environmental region (8), which are provided by means of a camera (4) of the motor vehicle (1), including the steps of: recognizing a first object feature (24) in a first image (10) of the sequence, wherein the first object feature (24) describes at least a part of the object (9) in the environmental region (8), estimating a position of the object (9) in the environmental region (8) based on a predetermined movement model, which describes a movement of the object (9) in the environmental region (8), determining a prediction feature (26) in a second image (11) following the first image (10) in the sequence based on the first object feature (24) and based on the estimated position, determining a second object feature (25) in the second image (11), associating the second object feature (25) with the prediction feature (26) in the second image (11) if a

Abstract: A method for determining a state of a tailgate (9) of a pickup vehicle (1) by a camera system (2), includes capturing a cargo bed (5) of the pickup vehicle (1) in an image (8) captured by a camera (3), determining a first region of interest (ROI1) in the captured image (8) by an electronic computing device (4) of the camera system (2), wherein the first region of interest (ROI1) includes the potential tailgate (9) at least partially, determining a parameter optically characterizing the tailgate (9) depending on the captured image (8), analyzing the first region of interest (ROI1) with regard to the characterizing parameter, and determining a closed state of the tailgate (9) as state or determining an opened state of the tailgate (9) as state depending on the analysis of the first region of interest (ROI1). A computer program product, an electronic computing device (4) as well as a camera system (2) are also disclosed.

Abstract: A method for determining a camera parameter for a camera (3) of a camera system (2) of a pickup vehicle (1) includes capturing a cargo bed (5) of the pickup vehicle (1) in an image (18) captured by using the camera (3), determining at least one first cargo bed edge line of the cargo bed (5) by optical analysis of the captured image (18) by using an electronic computing device (4) of the camera system (3), providing a function parameter for a cost function (15) by analysis of at least one first cargo bed edge line by using a regression-analysis algorithm of a solver module (14) of the electronic computing device (4), and determining the camera parameter on the basis of the cost function (15) depending on the provided function parameter by using the electronic computing device (4). A computer program product, an electronic computing device (4) as well as a camera system (2) are also disclosed.

Abstract: The invention relates to a method for recognizing a raised object on the basis of images in an environmental region of a motor vehicle, comprising: capturing a first image from a first camera and a second image from a second camera, transforming the first and second images into a common reference system, forming gradients over pixel values of pixels along gradient lines in the transformed first and second images, summing gradients along parallel summation lines to form a gradient sum, determining a first pair of the maxima of the gradient sum in the transformed first image and a second pair of the maxima of the gradient sum in the transformed second image, recognizing the raised object, if at least one distance between the maxima of the first pair in the transformed first image deviates from a distance of the maxima of the corresponding second pair in the transformed second image.

Abstract: A clean version of the amended Abstract is shown as follows: The invention relates to a method for recognizing a raised object on the basis of images in an environmental region of a motor vehicle, comprising: capturing a first image from a first camera and a second image from a second camera, transforming the first and second images into a common reference system, forming gradients over pixel values of pixels along gradient lines in the transformed first and second images, summing gradients along parallel summation lines to form a gradient sum, determining a first pair of the maxima of the gradient sum in the transformed first image and a second pair of the maxima of the gradient sum in the transformed second image, recognizing the raised object, if at least one distance between the maxima of the first pair in the transformed first image deviates from a distance of the maxima of the corresponding second pair in the transformed second image.

Abstract: The invention relates to a method for capturing an object (9) in an environmental region (8) of a motor vehicle (1) based on a sequence of images (10, 11) of the environmental region (8), which are provided by means of a camera (4) of the motor vehicle (1), including the steps of: recognizing a first object feature (24) in a first image (10) of the sequence, wherein the first object feature (24) describes at least a part of the object (9) in the environmental region (8), estimating a position of the object (9) in the environmental region (8) based on a predetermined movement model, which describes a movement of the object (9) in the environmental region (8), determining a prediction feature (26) in a second image (11) following the first image (10) in the sequence based on the first object feature (24) and based on the estimated position, determining a second object feature (25) in the second image (11), associating the second object feature (25) with the prediction feature (26) in the second image (11) if a

Abstract: The invention relates to a method for operating a driver assistance system (2) of a motor vehicle (1), in which a rear image of an environmental region (11, 12, 14) of the motor vehicle (1) located substantially next to and/or behind the motor vehicle (1) is captured by at least one camera (3, 4) of the driver assistance system (2), the camera being provided on the vehicle, wherein at least one road marking (19) of a roadway (17) is recognized in the environmental region (11, 12, 14) based on the captured rear image.

Abstract: The invention relates to a method for recognizing a covered state of a camera (4) of a motor vehicle (1) by providing an image of an environmental region of the motor vehicle (1) by means of the camera (4), determining respective brightness values of pixels within at least one image region of the image, determining a number of pixels within the at least one image region, which satisfy a preset criterion with respect to the brightness values, and checking whether the camera (4) is covered or not covered depending on the number.

Abstract: A method for operating a driver assistance system of a motor vehicle is provided. A first image sequence of a first rear environmental region of the motor vehicle is provided by a first camera system of an electronic rearview mirror and the first image sequence is displayed on a display device of the electronic rearview mirror disposed in an interior of the motor vehicle. Furthermore, a second image sequence of a second environmental region of the motor vehicle, which overlaps with the first environmental region at least in certain areas, is provided by a second camera system of an environmental capturing device. The electronic rearview mirror is then checked for presence of a malfunction by a computing device of the driver assistance system and the second image sequence is displayed on the display device of the electronic rearview mirror when the malfunction is present.

Abstract: A method for operating a driver assistance system of a motor vehicle is provided. A first image sequence of a first rear environmental region of the motor vehicle is provided by a first camera system of an electronic rearview mirror and the first image sequence is displayed on a display device of the electronic rearview mirror disposed in an interior of the motor vehicle. Furthermore, a second image sequence of a second environmental region of the motor vehicle, which overlaps with the first environmental region at least in certain areas, is provided by a second camera system of an environmental capturing device. The electronic rearview mirror is then checked for presence of a malfunction by a computing device of the driver assistance system and the second image sequence is displayed on the display device of the electronic rearview mirror when the malfunction is present.

Abstract: The invention relates to a method for operating a driver assistance device (2) in a motor vehicle (1), in which an image (15) of an environmental region (12) of the motor vehicle (1) is captured by means of a camera (11) of the driver assistance device (2) and in addition sensor data is captured to the environmental region (12) by means of a sensor (3 to 6) different from the camera (11), wherein an object (16) located in the environmental region (12) is identified in the image (15) by means of an electronic computing device of the driver assistance device (2) and the sensor data of the sensor (3 to 6) is used for identifying the object (16) in the image (15).