Abstract

We propose a new object matching algorithm which can separate overlapping objects and which is robust against erroneous data. The algorithm is based on the well-known iterative closest point (ICP) algorithm. However all published contributions to the ICP algorithm can not provide a proper segmentation of the input data. A fuzzy ICP algorithm can handle these problems by a fuzzy membership valuation at each iteration level. Furthermore, we introduce an evidence accumulation algorithm which allows a determination of the best match. In combination with search routines for the most common CAD models we provide powerful and efficient tools for CAD based object recognition systems.

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