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Classifying Objects from Visual Information

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dc.creator Bobick, Aaron
dc.creator Richards, Whitman
dc.date 2004-10-04T14:56:29Z
dc.date 2004-10-04T14:56:29Z
dc.date 1986-06-01
dc.date.accessioned 2013-10-09T02:45:28Z
dc.date.available 2013-10-09T02:45:28Z
dc.date.issued 2013-10-09
dc.identifier AIM-879
dc.identifier http://hdl.handle.net/1721.1/6443
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description Consider a world of 'objects.' Our goal is to place these objects into categories that are useful to the observer using sensory data. One criterion for utility is that the categories allow the observer to infer the object's potential behaviors, which are often non-observable. Under what condidtions can such useful categories be created? We propose a solution which requires 1.) that modes or clusters of natural structures are present in the world, and, 2.) that the physical properties of these structures are reflected in the sensory data used by the observer for classification. Given these two constraints, we explore the type of additional knowledge sufficient for the observer to generate an internal representation that makes explicit the natural modes. Finally we develop a formal expression of the object classification problem.
dc.format 3781558 bytes
dc.format 2953807 bytes
dc.format application/postscript
dc.format application/pdf
dc.language en_US
dc.relation AIM-879
dc.title Classifying Objects from Visual Information


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