Abstract: A method for calibrating the position and orientation of a camera, in particular a vehicle-mounted camera, relative to a calibration pattern includes the steps of: A] acquiring an image of the calibration pattern by the camera; B] determining a parameter of the image or of the calibration pattern; C] transforming the image based on the parameter; D] identifying characteristic points or possible characteristic points of the calibration pattern within the transformed image; E] deriving the position or orientation of the camera relative to the calibration pattern from the identified characteristic points or possible characteristic points; F] in dependence of a confidence value of the derived position or orientation of the camera or in dependence of the number of iterations of steps B to F so far, repeating steps B to F; and G] outputting the position or orientation of the camera derived in the last iteration of step E.

Abstract: A method for calibrating the position and orientation of a camera, in particular a vehicle-mounted camera, relative to a calibration pattern includes the steps of: A] acquiring an image of the calibration pattern by the camera; B] determining a parameter of the image or of the calibration pattern; C] transforming the image based on the parameter; D] identifying characteristic points or possible characteristic points of the calibration pattern within the transformed image; E] deriving the position or orientation of the camera relative to the calibration pattern from the identified characteristic points or possible characteristic points; F] in dependence of a confidence value of the derived position or orientation of the camera or in dependence of the number of iterations of steps B to F so far, repeating steps B to F; and G] outputting the position or orientation of the camera derived in the last iteration of step E.

Abstract: A method for calibrating the position and/or orientation of a camera, in particular a camera mounted to a vehicle such as a truck, relative to a calibration pattern includes the steps of: A] acquiring an image of the calibration pattern by means of the camera; B] determining at least one parameter of the image and/or of the calibration pattern or a sub-pattern of the calibration pattern as it appears in the image; C] transforming the image based on the at least one parameter; D] identifying characteristic points or possible characteristic points of the calibration pattern within the transformed image of the calibration pattern; E] deriving the position and/or orientation of the camera relative to the calibration pattern from the identified characteristic points or possible characteristic points; F] in dependence of a confidence value of the derived position and/or orientation of the camera and/or in dependence of the number of iterations of steps B to F so far, repeating steps B to F, wherein in step B the de

Abstract: Calibrating the orientation of a camera mounted to a vehicle includes providing calibration pattern defining at least two horizontal lines and two vertical lines; acquiring an image of the calibration pattern by means of the camera, the image having a first axis and a second axis corresponding to a horizontal axis and a vertical axis, respectively; identifying the horizontal lines and the vertical lines within the image; determining a horizontal vanishing point from the representations of the horizontal lines; determining a vertical vanishing point from the representations of the vertical lines; calculating a roll angle from the location of the horizontal vanishing point based on the image, calculating a yaw angle from a first coordinate of the horizontal vanishing point measured along the first axis, and calculating a pitch angle from a second coordinate of the vertical vanishing point measured along the second axis.

Abstract: This document describes an improved method for identifying of characteristic points of a calibration pattern within a set of candidate points in an image of the calibration pattern. The method includes scaling a template arrangement of template points that corresponds to the calibration pattern to an initial size. The method uses the scaled template arrangement to determine potential characteristic points. The method then determines whether the potential characteristic points meet a termination criterion. If the termination criterion is not met, the scaling of the template arrangement is modified and the previous step and this step are repeated. If the termination criterion is met, the potential characteristic points are identified as the characteristic points. In this way, the described method provides a robust means to automatically identify the characteristic points in the image of the calibration pattern without having to determine the distance between a camera and the calibration pattern.

Abstract: A method for identification of characteristic points of a calibration pattern within an image includes: (i) overlaying a template arrangement of template points over the candidate point such that a principal point of the template points coincides with the candidate point, wherein the template arrangement corresponds to the calibration pattern or to a sub-pattern of the calibration pattern, (ii) for each template point of the template arrangement, except the principal point, identifying from the set of candidate points the candidate point closest to the template point, and (iii) determining a degree of deviation by summing the distances between each template point of the template arrangement, except the principal point, and the candidate point closest to this template point; and identifying as characteristic points of the calibration pattern all those candidate points of the set of candidate points with a degree of deviation below a deviation threshold.

Abstract: A method for identification of candidate points as possible characteristic points of a calibration pattern within an image of the calibration pattern includes the steps of determining spots within a filtered image de-rived from the image of the calibration pattern, with a spot being defined as a coherent set of pixels of the filtered image having pixel values exceeding a threshold; for each determined spot, calculating a central point of the determined spot; and identifying as candidate points all calculated central points.

Abstract: A method for calibrating the position and/or orientation of a camera, in particular a camera mounted to a vehicle such as a truck, relative to a calibration pattern includes the steps of: A] acquiring an image of the calibration pattern by means of the camera; B] determining at least one parameter of the image and/or of the calibration pattern or a sub-pattern of the calibration pattern as it appears in the image; C] transforming the image based on the at least one parameter; D] identifying characteristic points or possible characteristic points of the calibration pattern within the transformed image of the calibration pattern; E] deriving the position and/or orientation of the camera relative to the calibration pattern from the identified characteristic points or possible characteristic points; F] in dependence of a confidence value of the derived position and/or orientation of the camera and/or in dependence of the number of iterations of steps B to F so far, repeating steps B to F, wherein in step B the de

Abstract: A method for identification of characteristic points of a calibration pattern within a set of candidate points derived from an image of the calibration pattern includes the steps of: A. scaling a template arrangement of template points which corresponds to the calibration pattern or to a sub-pattern of the calibration pattern to an initial size; B.

Abstract: Calibrating the orientation of a camera mounted to a vehicle includes providing calibration pattern defining at least two horizontal lines and two vertical lines; acquiring an image of the calibration pattern by means of the camera, the image having a first axis and a second axis corresponding to a horizontal axis and a vertical axis, respectively; identifying the horizontal lines and the vertical lines within the image; determining a horizontal vanishing point from the representations of the horizontal lines; determining a vertical vanishing point from the representations of the vertical lines; calculating a roll angle from the location of the horizontal vanishing point based on the image, calculating a yaw angle from a first coordinate of the horizontal vanishing point measured along the first axis, and calculating a pitch angle from a second coordinate of the vertical vanishing point measured along the second axis.

Abstract: A method for identification of characteristic points of a calibration pattern within an image includes: (i) overlaying a template arrangement of template points over the candidate point such that a principal point of the template points coincides with the candidate point, wherein the template arrangement corresponds to the calibration pattern or to a sub-pattern of the calibration pattern, (ii) for each template point of the template arrangement, except the principal point, identifying from the set of candidate points the candidate point closest to the template point, and (iii) determining a degree of deviation by summing the distances between each template point of the template arrangement, except the principal point, and the candidate point closest to this template point; and identifying as characteristic points of the calibration pattern all those candidate points of the set of candidate points with a degree of deviation below a deviation threshold.

Abstract: A method for identification of candidate points as possible characteristic points of a calibration pattern within an image of the calibration pat-tern includes the steps of determining spots within a filtered image de-rived from the image of the calibration pattern, with a spot being defined as a coherent set of pixels of the filtered image having pixel values exceeding a threshold; for each determined spot, calculating a central point of the determined spot; and identifying as candidate points all calculated central points.