Learning Shape Descriptions: Generating and Generalizing Models of Visual Objects

Title: en_US Learning Shape Descriptions: Generating and Generalizing Models of Visual Objects
Creator: en_US Connell, Jonathan Hudson
Date: 2004-10-20T20:03:37Z
Date Available: 2004-10-20T20:03:37Z
Date Issued: en_US 1985-09-01
Identifier: en_US AITR-853
uri: http://hdl.handle.net/1721.1/6870
Abstract: en_US We present the results of an implemented system for learning structural prototypes from grey-scale images. We show how to divide an object into subparts and how to encode the properties of these subparts and the relations between them. We discuss the importance of hierarchy and grouping in representing objects and show how a notion of visual similarities can be embedded in the description language. Finally we exhibit a learning algorithm that forms class models from the descriptions produced and uses these models to recognize new members of the class.
Extent: en_US 101 p.; 10686540 bytes; 4012801 bytes
Format: application/postscript; application/pdf
Language: en_US
Relation: en_US AITR-853