Self-service checkout terminal (100 to 300), comprising: • an image capture device configured to capture image data of a capture region; • a product capture device for capturing a product identifier of a product in the capture region when the product is presented to the product capture device; • a control device configured: for determining payment information on the basis of the product identifier; for determining (401, 705) a movement pattern on the basis of the image data and on the basis of depth information of the capture region, wherein the movement pattern represents a movement in the capture region and wherein determining the movement pattern comprises filtering the image data of the capture region on the basis of the depth information; for determining an indication about a trustworthiness of the payment information on the basis of the movement pattern; wherein determining (401, 705) the movement pattern comprises classifying the image data on the basis of the filtered image data, preferably by means of object recognition; wherein the classifying comprises assigning one class from a plurality of classes to the image data, of which classes one class represents the product being arranged in a partial region (311a, 311b, 311c) of the capture region and an additional class represents the partial region (311a, 311b, 311c) being empty; wherein the classifying is effected by means of a classifier and the classifier is configured as a convolutional neural network; wherein the classifier comprises an input layer and image data are received in the input layer and the incoming image data are represented by means of a matrix and the matrix comprises a first spatial coordinate in a first dimension, a second spatial coordinate in a second dimension, color information in a third dimension and depth information in a fourth dimension. • an image capture device configured to capture image data of a capture region; • a product capture device for capturing a product identifier of a product in the capture region when the product is presented to the product capture device; • a control device configured: for determining payment information on the basis of the product identifier; for determining (401, 705) a movement pattern on the basis of the image data and on the basis of depth information of the capture region, wherein the movement pattern represents a movement in the capture region and wherein determining the movement pattern comprises filtering the image data of the capture region on the basis of the depth information; for determining an indication about a trustworthiness of the payment information on the basis of the movement pattern; wherein determining (401, 705) the movement pattern comprises classifying the image data on the basis of the filtered image data, preferably by means of object recognition; wherein the classifying comprises assigning one class from a plurality of classes to the image data, of which classes one class represents the product being arranged in a partial region (311a, 311b, 311c) of the capture region and an additional class represents the partial region (311a, 311b, 311c) being empty; wherein the classifying is effected by means of a classifier and the classifier is configured as a convolutional neural network; wherein the classifier comprises an input layer and image data are received in the input layer and the incoming image data are represented by means of a matrix and the matrix comprises a first spatial coordinate in a first dimension, a second spatial coordinate in a second dimension, color information in a third dimension and depth information in a fourth dimension. for determining payment information on the basis of the product identifier; for determining (401, 705) a movement pattern on the basis of the image data and on the basis of depth information of the capture region, wherein the movement pattern represents a movement in the capture region and wherein determining the movement pattern comprises filtering the image data of the capture region on the basis of the depth information; for determining an indication about a trustworthiness of the payment information on the basis of the movement pattern; wherein determining (401, 705) the movement pattern comprises classifying the image data on the basis of the filtered image data, preferably by means of object recognition; wherein the classifying comprises assigning one class from a plurality of classes to the image data, of which classes one class represents the product being arranged in a partial region (311a, 311b, 311c) of the capture region and an additional class represents the partial region (311a, 311b, 311c) being empty; wherein the classifying is effected by means of a classifier and the classifier is configured as a convolutional neural network; wherein the classifier comprises an input layer and image data are received in the input layer and the incoming image data are represented by means of a matrix and the matrix comprises a first spatial coordinate in a first dimension, a second spatial coordinate in a second dimension, color information in a third dimension and depth information in a fourth dimension.