1. A method for real-time-capable computer-assisted analysis of an image sequence containing a variable pose of an object composed of interconnected elements movable in relation to each other, wherein the frames of the image sequence have been recorded by a distance measuring camera and are processed by a computer and the frames have brightness and distance data as functions of pixel coordinates of the camera for each frame of the sequence; the method comprising: (a) the computer detecting the pixels of a frame which map the object; (b) the computer calculating a three-dimensional (3D) aggregate of points within a virtual space, which represents that surface of the object which is visible for the camera, by calculated projection of object-mapping pixels into such a space, taking into account acquired data of a distance from the object; (c) the computer fitting a model of the object, which consists of nodes and edges, into the computer-generated 3D aggregate of points for the frame, the nodes representing a selection of elements of the object and the edges representing interconnections of these elements; (d) the computer iteratively updating all node positions by using a learning rule for training a self-organizing map with a predetermined number of randomly sampled points of the aggregate of points; (e) repeating at least 25 times per second the steps (a) through (d) for each subsequent frame of the sequence, the result of step (d) of the preceding frame being used respectively for the fitting process in step (c); (f) the computer determining the changing pose from positions of predetermined nodes of the model, which have been detected in at least representative frames of the image sequence; (g) wherein the node positions of the model are updated in iteration steps, one point x being randomly sampled for the predetermined number of points of the 3D aggregate of points in each iteration step and all nodes being shifted towards x; and (h) the degree of the shift being largest for the node which had the smallest distance from x prior to the iteration step wherein the number of the randomly sampled points x or that of the iteration steps is about 10% of the total number of the points within the aggregate of points.