Abstract: A method for recognizing one or more objects represented in an image by an M-dimensional point cloud, composed of n points, includes: determining, for each of a number m>0, of specific one-dimensional variables, an associated value of the variable for each of the points on the basis of the position or properties of the point; determining, for each of the variables, a frequency distribution with respect to the respective values of said variable; approximating each of the frequency distributions by a linear combination of a finite number of one-dimensional probability density functions associated with the variable; segmenting the image such that each product of in probability density functions is uniquely assigned a segment of the image; assigning each point of the point cloud to the segment; and identifying at least one of the segments to which at least a predefined minimum number of points was assigned.