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IEEE Transactions on Pattern Analysis and Machine Intelligence
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Communications of the ACM
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Communications of the ACM
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Communications of the ACM
Recognizing Planar Objects Using Invariant Image Features
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Machine Learning
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IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Learning
Shape Understanding System: Learning of the Visual Concepts
ISAS-SCI '01 Proceedings of the World Multiconference on Systemics, Cybernetics and Informatics: Information Systems Development-Volume I - Volume I
Shape Understanding System: The Noisy Class
ISAS-SCI '01 Proceedings of the World Multiconference on Systemics, Cybernetics and Informatics: Information Systems Development-Volume I - Volume I
Model-Based Object Recognition - A Survey of Recent Research
Model-Based Object Recognition - A Survey of Recent Research
Understanding the curve-polygon object
Computers and Graphics
Understanding the curve-polygon object
Computers and Graphics
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Abstract--In this paper, a method of knowledge generation as part of a shape-understanding method is presented. The proposed method of knowledge generation consists of: learning the description of new a posteriori classes, learning the concept of visual objects, and generation of the visual representation of "inner驴 objects. The visual concept, as part of the concept of the visual object, is expressed as a set of symbolic names that refers to possible classes of shape. The visual concept can be used to find the visual similarities between different visual objects, perform visual transformations as part of visual thinking capabilities of a system, and memorize a visual object as a symbolic representation. The knowledge obtained in the process of knowledge generation is integrated with an existing knowledge of a shape understanding system and used in the explanatory process. This system of shape understanding (SUS), that is, the implementation of the shape understanding method, is designed to imitate the visual thinking capabilities of the human visual system. The SUS consists of different types of experts that perform different processing and reasoning tasks and is designed to perform visual diagnosis in medical applications.