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• W2006095608 abstract "The topic of model-building for 3-D objects is examined. Most 3-D object recognition systems construct models either manually or by training. Neither approach has been very satisfactory, particularly in designing object recognition systems which can handle a large number of objects. Recent interest in integrating mechanical CAD systems and vision systems has led to a third type of model building for vision: adaptation of preexisting CAD models of objects for recognition. If a solid model of an object to be recognized is already available in a manufacturing database, then it should be possible to infer automatically a model appropriate for vision tasks from the manufacturing model. Such a system has been developed. It uses 3-D object descriptions created on a commercial CAD system and expressed in both the industry-standard IGES form and a polyhedral approximation and performs geometric inferencing to obtain a relational graph representation of the object which can be stored in a database of models for object recognition. Relational graph models contain both view-independent information extracted from the IGES description and view-dependent information (patch areas) extracted from synthetic views of the object. It is argued that such a system is needed to efficiently create a large database (more than 100 objects) of 3-D models to evaluate matching strategies.< <ETX xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>></ETX>" @default.
• W2006095608 created "2016-06-24" @default.
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• W2006095608 date "1991-02-01" @default.
• W2006095608 modified "2023-10-14" @default.
• W2006095608 title "CAD-based computer vision: from CAD models to relational graphs" @default.
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• W2006095608 doi "https://doi.org/10.1109/34.67642" @default.
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