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Limitations of Non Model-Based Recognition Schemes

Author(s)
Moses, Yael; Ullman, Shimon
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Abstract
Different approaches to visual object recognition can be divided into two general classes: model-based vs. non model-based schemes. In this paper we establish some limitation on the class of non model-based recognition schemes. We show that every function that is invariant to viewing position of all objects is the trivial (constant) function. It follows that every consistent recognition scheme for recognizing all 3-D objects must in general be model based. The result is extended to recognition schemes that are imperfect (allowed to make mistakes) or restricted to certain classes of objects.
Date issued
1991-05-01
URI
http://hdl.handle.net/1721.1/6571
Other identifiers
AIM-1301
Series/Report no.
AIM-1301

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  • AI Memos (1959 - 2004)

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