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<p>The authors describe techniques that generate multiple interpretations from dense range images of piles of unknown objects and methods that use physical law, such as object stability, to rank the interpretations. Each of the interpretations completely accounts for the observed range data, but the interpretations differ in the ways visible portions of objects are extended into the occluded portions of the scene. Experiments with 100 range images indicate that the techniques are fairly robust when the scenes consist of shapes that are approximately prismatic or cylindrical. These techniques are based on novel approaches in several key areas, including explicit use of sensor geometry, generic shape models to synthesize scene descriptions, spatial-reasoning techniques that incorporate knowledge about the laws of physics, direct estimation of the physical properties of the objects in the scene, and detection and refinement of descriptions of approximately planar or cylindrical surfaces.</p>
object configurations understanding; pattern recognition; image interpretation; computer vision; spatial reasoning; range images; sensor geometry; generic shape models; scene descriptions; computer vision; pattern recognition; spatial reasoning

P. Molgaonkar, C. Cowan and J. DeCurtins, "Understanding Object Configurations using Range Images," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 14, no. , pp. 303-307, 1992.
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