Natural Object Categorization

Item

Title
en_US Natural Object Categorization
Creator
en_US Bobick, Aaron F.
Date
2004-10-20T20:11:10Z
Date Available
2004-10-20T20:11:10Z
Date Issued
en_US 1987-11-01
Identifier
en_US AITR-1001
uri
http://hdl.handle.net/1721.1/6964
Abstract
en_US This thesis addresses the problem of categorizing natural objects. To provide a criteria for categorization we propose that the purpose of a categorization is to support the inference of unobserved properties of objects from the observed properties. Because no such set of categories can be constructed in an arbitrary world, we present the Principle of Natural Modes as a claim about the structure of the world. We first define an evaluation function that measures how well a set of categories supports the inference goals of the observer. Entropy measures for property uncertainty and category uncertainty are combined through a free parameter that reflects the goals of the observer. Natural categorizations are shown to be those that are stable with respect to this free parameter. The evaluation function is tested in the domain of leaves and is found to be sensitive to the structure of the natural categories corresponding to the different species. We next develop a categorization paradigm that utilizes the categorization evaluation function in recovering natural categories. A statistical hypothesis generation algorithm is presented that is shown to be an effective categorization procedure. Examples drawn from several natural domains are presented, including data known to be a difficult test case for numerical categorization techniques. We next extend the categorization paradigm such that multiple levels of natural categories are recovered; by means of recursively invoking the categorization procedure both the genera and species are recovered in a population of anaerobic bacteria. Finally, a method is presented for evaluating the utility of features in recovering natural categories. This method also provides a mechanism for determining which features are constrained by the different processes present in a multiple modal world.
Extent
16885823 bytes
13169061 bytes
Format
application/postscript
application/pdf
Language
en_US
Relation
en_US AITR-1001
Item sets
AI Technical Reports (1964 - 2004)