Abstract: A driving assistance method for a vehicle, in which in a training phase, the vehicle is steered by a driver through a setpoint course to a setpoint destination position, and setpoint course data are gathered in the process, in a replay phase, the vehicle is steered automatically through an actual course, actual course data are gathered in the process and, via a comparison of actual course data to setpoint course data, the steering of the vehicle is carried out so that the actual course is adapted/being adapted to the setpoint course and ends in an area of the setpoint destination position; and images of the vehicle surroundings are recorded with a camera as setpoint course data at setpoint positions, spaced equidistantly on a setpoint driving route of the setpoint course, and edge segments, feature points and corresponding descriptors are determined from an image processing for each image.

Abstract: A method in a training phase includes acquiring a first image of an environment of a means of locomotion from a first position, using an optical sensor; acquiring a second image of the environment of the means of locomotion from a second position, differing from the first position, using the optical sensor; ascertaining features that represent the first image and ascertaining features that represent the second image using an algorithm for feature extraction; selecting those features of the first and the second image which do not meet a predefined rating criterion; and ascertaining significant similarities between the selected features of the first and the second image and storing references that represent the significant similarities. A method is performed in an execution phase that makes use of the stored features of the training phase.

Abstract: A driving assistance method for a vehicle, in which in a training phase, the vehicle is steered by a driver through a setpoint course to a setpoint destination position, and setpoint course data are gathered in the process, in a replay phase, the vehicle is steered automatically through an actual course, actual course data are gathered in the process and, via a comparison of actual course data to setpoint course data, the steering of the vehicle is carried out so that the actual course is adapted/being adapted to the setpoint course and ends in an area of the setpoint destination position; and images of the vehicle surroundings are recorded with a camera as setpoint course data at setpoint positions, spaced equidistantly on a setpoint driving route of the setpoint course, and edge segments, feature points and corresponding descriptors are determined from an image processing for each image.

Abstract: A method in a training phase includes acquiring a first image of an environment of a means of locomotion from a first position, using an optical sensor; acquiring a second image of the environment of the means of locomotion from a second position, differing from the first position, using the optical sensor; ascertaining features that represent the first image and ascertaining features that represent the second image using an algorithm for feature extraction; selecting those features of the first and the second image which do not meet a predefined rating criterion; and ascertaining significant similarities between the selected features of the first and the second image and storing references that represent the significant similarities. A method is performed in an execution phase that makes use of the stored features of the training phase.