A computer-implemented method for monitoring a spatial area in a personnel interlock, in particular for monitoring the separation of persons with respect to the spatial area, the method comprising: receiving image data representing a plurality of depth images of the spatial area, which are acquired simultaneously and from different positions in the area of the personnel interlock, each by means of a respective 3D image sensor (8a, 8b) arranged at the respective position, wherein each of the depth images indicates, for each of its pixels, a spatial distance of the object or object portion depicted thereon from the respective 3D image sensor (8a, 8b) based on a pixel value assigned thereto; calculating, for each of the depth images, a characteristic depth image value associated with the respective depth image based on all of the individual pixel values or a subset of the individual pixel values of the respective depth image, using an averaging method; calculating a total image value by combining the characteristic depth image values of the various depth images according to a predetermined monotonic combination rule, wherein a combination rule is to be understood as a rule for determining a result value from a plurality of input values, specifically depth image values in the present case, which has a monotonicity property in the sense that the result value is either (i) always greater than or equal to each of the input values or, alternatively, (ii) always less than or equal to each of the input values; and determining an estimation result for the probability that more than one person (P1, P2) is present in the spatial area, depending on the result of a comparison of the total image value with at least one predetermined reference total image value. receiving image data representing a plurality of depth images of the spatial area, which are acquired simultaneously and from different positions in the area of the personnel interlock, each by means of a respective 3D image sensor (8a, 8b) arranged at the respective position, wherein each of the depth images indicates, for each of its pixels, a spatial distance of the object or object portion depicted thereon from the respective 3D image sensor (8a, 8b) based on a pixel value assigned thereto; calculating, for each of the depth images, a characteristic depth image value associated with the respective depth image based on all of the individual pixel values or a subset of the individual pixel values of the respective depth image, using an averaging method; calculating a total image value by combining the characteristic depth image values of the various depth images according to a predetermined monotonic combination rule, wherein a combination rule is to be understood as a rule for determining a result value from a plurality of input values, specifically depth image values in the present case, which has a monotonicity property in the sense that the result value is either (i) always greater than or equal to each of the input values or, alternatively, (ii) always less than or equal to each of the input values; and determining an estimation result for the probability that more than one person (P1, P2) is present in the spatial area, depending on the result of a comparison of the total image value with at least one predetermined reference total image value.