Data Driven Spatial Reasoning
Annual rept. 1 Oct 90-30 Sep 91,
SRI INTERNATIONAL MENLO PARK CA
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Our research is aimed at the development of computational techniques for hypothesizing the shapes of hidden portions of unknown objects within a pile of such objects, using a dense range image of the pile. The techniques that we have developed employ symmetry, stability, viewpoint independence, and object impenetrability to hypothesize the unknown shape and dimensions of each visible object. The process constructs alternative hypotheses, which differ in the way the visible portions of objects are extended into the occluded regions within the scene. To ensure that each interpretation is consistent with the observed range data, the known geometry of the range sensor is used in forming the hypotheses. The final result is one or more hypothesized object configurations, each of which is consistent with both the sensed range data and the physical constraints between objects in contact.