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Recognizing 3-D Objects Using 2-D Images

Author(s)
Jacobs, David W.
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Abstract
We discuss a strategy for visual recognition by forming groups of salient image features, and then using these groups to index into a data base to find all of the matching groups of model features. We discuss the most space efficient possible method of representing 3-D models for indexing from 2-D data, and show how to account for sensing error when indexing. We also present a convex grouping method that is robust and efficient, both theoretically and in practice. Finally, we combine these modules into a complete recognition system, and test its performance on many real images.
Date issued
1993-04-01
URI
http://hdl.handle.net/1721.1/6796
Other identifiers
AITR-1416
Series/Report no.
AITR-1416
Keywords
grouping, indexing, recognition, invariants, sensing erro, snon-accidental properties

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