Abstract: The present application relates to a method for vehicle hinge point calibration, comprising: acquiring a raw image of a first portion and a second portion hinged to one another of a vehicle; adjusting, stitching and cropping the raw image to obtain respective independent surround-view images of the first portion and the second portion; and at least on the basis of the independent surround-view images of the first portion and the second portion, calculating the angle of rotation and the corresponding translation vector between the first and second portions, and thus calculating the coordinates of the respective hinge points of the first and second portions. Further comprised in the present application are an apparatus for vehicle hinge point calibration, a computer device, and a computer-readable storage medium.

Abstract: A camera pose information detection method, includes collecting a plurality of images by means of a multi-lens camera, and determining a road surface region image based on the plurality of images; and projecting points in the road surface region image onto a camera coordinate system, so as to obtain camera pose information.

Abstract: The present application relates to a method for vehicle hinge point calibration, comprising: acquiring a raw image of a first portion and a second portion hinged to one another of a vehicle; adjusting, stitching and cropping the raw image to obtain respective independent surround-view images of the first portion and the second portion; and at least on the basis of the independent surround-view images of the first portion and the second portion, calculating the angle of rotation and the corresponding translation vector between the first and second portions, and thus calculating the coordinates of the respective hinge points of the first and second portions. Further comprised in the present application are an apparatus for vehicle hinge point calibration, a computer device, and a computer-readable storage medium.

Abstract: The present disclosure relates to a method for generating a panoramic surround view image of a vehicle, comprising: acquiring actual original images of external environment of a first part and a second part of the vehicle hinged to each other; processing the actual original images to obtain respective actual independent surround view images of the first part and the second part; obtaining coordinates of respective hinge points of the first part and the second part; determining matched feature point pairs in the actual independent surround view images of the first part and the second pan; calculating a distance between two points in each matched feature point pair accordingly, and taking matched feature point pairs with the distance less than a preset first threshold as a successfully matched feature point pairs; and taking a rotation angle corresponding to the maximum number of the successfully matched feature point pairs as a candidate rotation angle of the first part relative to the second part.

Abstract: The present application relates to a method for vehicle hinge point calibration, comprising: acquiring a raw image of a first portion and a second portion hinged to one another of a vehicle; adjusting, stitching and cropping the raw image to obtain respective independent surround-view images of the first portion and the second portion; and at least on the basis of the independent surround-view images of the first portion and the second portion, calculating the angle of rotation and the corresponding translation vector between the first and second portions, and thus calculating the coordinates of the respective hinge points of the first and second portions. Further comprised in the present application are an apparatus for vehicle hinge point calibration, a computer device, and a computer-readable storage medium.

Abstract: The present disclosure relates to a method for generating a panoramic surround view image of a vehicle, comprising: acquiring actual original images of external environment of a first part and a second part of the vehicle hinged to each other; processing the actual original images to obtain respective actual independent surround view images of the first part and the second part; obtaining coordinates of respective hinge points of the first part and the second part; determining matched feature point pairs in the actual independent surround view images of the first part and the second pan; calculating a distance between two points in each matched feature point pair accordingly, and taking matched feature point pairs with the distance less than a preset first threshold as a successfully matched feature point pairs; and taking a rotation angle corresponding to the maximum number of the successfully matched feature point pairs as a candidate rotation angle of the first part relative to the second part.

Abstract: A camera pose information detection method, includes collecting a plurality of images by means of a multi-lens camera, and determining a road surface region image based on the plurality of images; and projecting points in the road surface region image onto a camera coordinate system, so as to obtain camera pose information.