Computer-implemented method for checking the plausibility of a flow-vector hypothesis, comprising: - determining a prediction vector, associated with a feature, based on a movement of the feature between a first image and a second image, wherein the second image is an image following the first image in a sequence of images, - generating a hypothesis vector, which is associated with the feature and describes a probable movement of the feature between the second image and a third image, wherein the third image is an image following the second image in a sequence of images, - calculating a degree of similarity between the prediction vector and the hypothesis vector based on a difference between the prediction vector and the hypothesis vector, wherein, when calculating the degree of similarity between the prediction vector and the hypothesis vector, a deviation in the orthogonal direction with respect to the prediction vector is evaluated more strictly than a deviation in the longitudinal direction with respect to the prediction vector, or a deviation in the orthogonal direction with respect to the hypothesis vector is evaluated more strictly than a deviation in the longitudinal direction with respect to the hypothesis vector, and - evaluating a plausibility of the hypothesis vector based on the calculated degree of similarity, wherein it is evaluated whether the hypothesis vector describes an actual movement of the feature between the second image and the third image, characterized in that - when calculating the degree of similarity, the difference is determined by means of a difference vector which is generated by forming a difference between the prediction vector and the hypothesis vector, wherein the difference is determined by means of two vector components (22, 23) of the difference vector, which represent a measure of the deviation in the orthogonal direction and a measure of the deviation in the longitudinal direction, wherein the two vector components (22, 23) are differently weighted. - determining a prediction vector, associated with a feature, based on a movement of the feature between a first image and a second image, wherein the second image is an image following the first image in a sequence of images, - generating a hypothesis vector, which is associated with the feature and describes a probable movement of the feature between the second image and a third image, wherein the third image is an image following the second image in a sequence of images, - calculating a degree of similarity between the prediction vector and the hypothesis vector based on a difference between the prediction vector and the hypothesis vector, wherein, when calculating the degree of similarity between the prediction vector and the hypothesis vector, a deviation in the orthogonal direction with respect to the prediction vector is evaluated more strictly than a deviation in the longitudinal direction with respect to the prediction vector, or a deviation in the orthogonal direction with respect to the hypothesis vector is evaluated more strictly than a deviation in the longitudinal direction with respect to the hypothesis vector, and - evaluating a plausibility of the hypothesis vector based on the calculated degree of similarity, wherein it is evaluated whether the hypothesis vector describes an actual movement of the feature between the second image and the third image, characterized in that - when calculating the degree of similarity, the difference is determined by means of a difference vector which is generated by forming a difference between the prediction vector and the hypothesis vector, wherein the difference is determined by means of two vector components (22, 23) of the difference vector, which represent a measure of the deviation in the orthogonal direction and a measure of the deviation in the longitudinal direction, wherein the two vector components (22, 23) are differently weighted.