Universität Zu Lübeck

Martin Haker

Thomas Martinetz

Erhardt Barth

The invention relates to a method for the real-time-capable, computer-assisted analysis of an image sequence of an object consisting of elements that can be moved relative to each other and are interconnected, said sequence containing a variable pose, wherein the individual images of the image sequence are recorded by way of a time-of-flight (TOF) camera such that said images can be processed by a computer, and contain brightness and distance data as functions of the pixel coordinates of the camera for each image of the sequence, comprising the following steps: a. Capturing the pixels of an individual image forming the object, b. calculating a three-dimensional (3D) point cloud in a virtual space, said point cloud representing the surface of the object that is visible to the camera, by a computational projection of object-depicting pixels in such a space, while taking captured distance data to the object into consideration, c. fitting a model of the object consisting of nodes and edges into the computer-generated 3D point cloud for the individual images, wherein the nodes represent a selection of elements of the object and the edges represent the connections of said elements amount each other, d. iteratively updating all node positions by applying a learning rule for training a self-organizing map having a previously defined number of randomly selected dots of the point cloud, e. repeating steps a. to d. for each subsequent individual image of the sequence, wherein for the fitting in step c. the result of step e. of the preceding image is used in each case, and f. determining the varying pose from the positions of predetermined nodes of the model which have been captured in at least representative images of the image sequence.

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Lübeck, Germany

Martin Haker