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dc.contributor.authorClemens, David T.en_US
dc.date.accessioned2004-10-20T20:23:24Z
dc.date.available2004-10-20T20:23:24Z
dc.date.issued1991-06-01en_US
dc.identifier.otherAITR-1307en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/7039
dc.description.abstractIn model-based vision, there are a huge number of possible ways to match model features to image features. In addition to model shape constraints, there are important match-independent constraints that can efficiently reduce the search without the combinatorics of matching. I demonstrate two specific modules in the context of a complete recognition system, Reggie. The first is a region-based grouping mechanism to find groups of image features that are likely to come from a single object. The second is an interpretive matching scheme to make explicit hypotheses about occlusion and instabilities in the image features.en_US
dc.format.extent22413823 bytes
dc.format.extent8247283 bytes
dc.format.mimetypeapplication/postscript
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.relation.ispartofseriesAITR-1307en_US
dc.titleRegion-Based Feature Interpretation for Recognizing 3D Models in 2D Imagesen_US


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