Recognizing 3-D Objects Using 2-D Images
dc.date.accessioned | 2004-10-20T19:55:20Z | |
dc.date.accessioned | 2018-11-24T10:21:53Z | |
dc.date.available | 2004-10-20T19:55:20Z | |
dc.date.available | 2018-11-24T10:21:53Z | |
dc.date.issued | 1993-04-01 | en_US |
dc.identifier.uri | http://hdl.handle.net/1721.1/6796 | |
dc.identifier.uri | http://repository.aust.edu.ng/xmlui/handle/1721.1/6796 | |
dc.description.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. | en_US |
dc.format.extent | 269 p. | en_US |
dc.format.extent | 3519825 bytes | |
dc.format.extent | 7005877 bytes | |
dc.language.iso | en_US | |
dc.subject | grouping | en_US |
dc.subject | indexing | en_US |
dc.subject | recognition | en_US |
dc.subject | invariants | en_US |
dc.subject | sensing erro | en_US |
dc.subject | snon-accidental properties | en_US |
dc.title | Recognizing 3-D Objects Using 2-D Images | en_US |
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