Abstract: The present disclosure relates to a method for determining the yaw angle of a trailer with respect to the longitudinal axis of a towing vehicle based on at least one feature included in multiple captured images by providing multiple algorithms for calculating at least one angle estimation.

Abstract: Determining the yaw angle of a trailer with respect to the longitudinal axis of a towing vehicle is disclosed. This includes capturing first and second images of the trailer using a camera. Trailer orientation with respect to the vehicle is different on the two images. First and second trailer features are determined which are visible on the two images. The first and second features are at different positions of the trailer. A first angle estimation is calculated characterizing the pivot angle in a horizontal plane between the first feature on the first image and the first feature on the second image relative to a towing vehicle fix point. A second angle estimation is calculated characterizing the pivot angle in a horizontal plane between the second feature on the first image and the second feature on the second image relative to the fix point. The yaw angle is calculated based on the first and second angle estimations.

Abstract: The present disclosure relates to a method for determining the yaw angle of a trailer with respect to the longitudinal axis of a towing vehicle based on a feature included in multiple captured images by establishing a perpendicular bisector.

Abstract: The present disclosure relates to a method for determining the yaw angle of a trailer with respect to the longitudinal axis of a towing vehicle based on at least one feature included in multiple captured images by using correction information.

Abstract: A method for calculating a tow hitch position of a trailer is presented. A first and a second image of the trailer is captured and a trailer rotation and translation relative to a known zero pose of the trailer based on the captured first and second images is calculated. The rotation axes of the trailer in the first and second image is calculated based on the calculated trailer rotations and translations. An intersection of the first and second rotation axis is calculated to determine a ray to the tow hitch position. The ray to the tow hitch position and a geometrical condition are used to calculate the tow hitch position.

Abstract: In a system and a method for extrinsic calibration of an image capture apparatus of a vehicle, the vehicle includes a vehicle body and a movable part configured to rotate around a known rotation axis relative to the vehicle body. The system includes an image capture apparatus having an image capture device mounted on the vehicle body and configured to capture at least two images of the movable part, an identification unit configured to identify at least two image features in the images, a calculation unit configured to calculate a calculated direction of the rotation axis relative to the image capture device based on the image features, and a calibration unit configured to determine extrinsic parameters of the image capture apparatus based on the calculated direction of the rotation axis relative to the image capture device and the known parameters of the rotation axis relative to the vehicle.

Abstract: A method for estimating a range of a moving object (MO) includes steps of capturing (S1) images of a surrounding by a camera (2), processing (S2) features of captured images to determine a bearing of a moving object (MO) based on a detected cluster of features belonging to the moving object (MO) within the captured images, and estimating (S3) a range of the moving object (MO) based on determined ground features belonging to a ground plane (GP) along the determined bearing of the moving object (MO) which are not occluded by the moving object (MO).

Abstract: A method for calculating a tow hitch position of a trailer is presented. A first and a second image of the trailer is captured and a trailer rotation and translation relative to a known zero pose of the trailer based on the captured first and second images is calculated. The rotation axes of the trailer in the first and second image is calculated based on the calculated trailer rotations and translations. An intersection of the first and second rotation axis is calculated to determine a ray to the tow hitch position. The ray to the tow hitch position and a geometrical condition are used to calculate the tow hitch position.

Abstract: In a system and a method for extrinsic calibration of an image capture system of a vehicle, the vehicle includes a body and a body portion, wherein the body portion is configured to rotate around a rotation axis relative to the vehicle. The system includes an image capture system with an image capture device mounted on the body portion and adapted to capture at least two images of the body and/or surrounding area of the vehicle, an identification unit adapted to identify at least two image features in the images, a calculation unit adapted to calculate a direction of the rotation axis relative to the image capture device based on the image features, and a calibration unit configured to determine extrinsic parameters of the image capture system based on the calculated direction of the rotation axis relative to the vehicle. The image capture system is calibrated using degrees of freedom of movement that the image capture device has due to being mounted on a movable portion of the vehicle.

Abstract: A method for estimating a range of a moving object (MO) includes steps of capturing (S1) images of a surrounding by a camera (2), processing (S2) features of captured images to determine a bearing of a moving object (MO) based on a detected cluster of features belonging to the moving object (MO) within the captured images, and estimating (S3) a range of the moving object (MO) based on determined ground features belonging to a ground plane (GP) along the determined bearing of the moving object (MO) which are not occluded by the moving object (MO).

Abstract: This disclosure relates to a method in which points common to two or more of the images that appear to represent the same real world features are identified, and changes in the location of the points between respective images are used to deduce the motion of the camera and to find the position of the real world features in three dimensional space. In order to determine the scale of the three dimensional information, the position of a reference feature, whose actual distance from the camera is known, is found from the images. The reference feature is found by considering only candidate points selected from candidate points falling within a portion of the image corresponding to a part of the field of view of the camera. The scale is determined from the distance between the camera and the reference feature in the image and in real life.

Abstract: This disclosure relates to a method in which points common to two or more of the images that appear to represent the same real world features are identified, and changes in the location of the points between respective images are used to deduce the motion of the camera and to find the position of the real world features in three dimensional space. In order to determine the scale of the three dimensional information, the position of a reference feature, whose actual distance from the camera is known, is found from the images. The reference feature is found by considering only candidate points selected from candidate points falling within a portion of the image corresponding to a part of the field of view of the camera. The scale is determined from the distance between the camera and the reference feature in the image and in real life.