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.
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/6796 |
| Date | 01 April 1993 |
| Creators | Jacobs, David W. |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | en_US |
| Detected Language | English |
| Format | 269 p., 3519825 bytes, 7005877 bytes, application/octet-stream, application/pdf |
| Relation | AITR-1416 |
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