1. A method for estimating position parameters of an object in space from a two-dimensional image using a Kohonen network having neurons, comprising the steps of: a) prescribing indexable weighting vectors m(i)=(m(i,1),. .. , m(i,M)) of a dimension M and positional parameters x(i)=(x(i,1),. .. , x(i,N)) of a dimension N, allocated to the weighting factors, by whole numbers i that unambiguously identify each neuron i of the Kohonen network; b) forming a pattern vector v=(v(1),. .. , v(k),. .. , v(M)) from two-dimensional coordinates p(k), g(k) of feature points in the image, whereby v(k) describes a respective feature point in the image in a respective form v(k)=(p(k),q(k)); c) applying the pattern vector v=(v(1),. .. v(k),. .. , v(M)) to each neuron i of the Kohonen network; d) calculating a respective output value a(i)=a(v,m(i)) for the applied pattern vector v=(v(1),. .. , v(k),. .. , v(M)) in each neuron i of the Kohonen network; and e) deriving sought positional parameters from respective positional parameters x(i)=(x(i, 1),. .. , x(i,N)) allocated to a neuron i having an optimum output value a(v,m(i)).