Statistical Object Recognition
Two formulations of model-based object recognition are described. MAP Model Matching evaluates joint hypotheses of match and pose, while Posterior Marginal Pose Estimation evaluates the pose only. Local search in pose space is carried out with the Expectation--Maximization (EM) algorithm. Rec...
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| Language: | en_US |
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2004
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| Online Access: | http://hdl.handle.net/1721.1/7046 |
| _version_ | 1826215532294045696 |
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| author | Wells, William M. III |
| author_facet | Wells, William M. III |
| author_sort | Wells, William M. III |
| collection | MIT |
| description | Two formulations of model-based object recognition are described. MAP Model Matching evaluates joint hypotheses of match and pose, while Posterior Marginal Pose Estimation evaluates the pose only. Local search in pose space is carried out with the Expectation--Maximization (EM) algorithm. Recognition experiments are described where the EM algorithm is used to refine and evaluate pose hypotheses in 2D and 3D. Initial hypotheses for the 2D experiments were generated by a simple indexing method: Angle Pair Indexing. The Linear Combination of Views method of Ullman and Basri is employed as the projection model in the 3D experiments. |
| first_indexed | 2024-09-23T16:33:49Z |
| id | mit-1721.1/7046 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T16:33:49Z |
| publishDate | 2004 |
| record_format | dspace |
| spelling | mit-1721.1/70462019-04-10T11:52:25Z Statistical Object Recognition Wells, William M. III Two formulations of model-based object recognition are described. MAP Model Matching evaluates joint hypotheses of match and pose, while Posterior Marginal Pose Estimation evaluates the pose only. Local search in pose space is carried out with the Expectation--Maximization (EM) algorithm. Recognition experiments are described where the EM algorithm is used to refine and evaluate pose hypotheses in 2D and 3D. Initial hypotheses for the 2D experiments were generated by a simple indexing method: Angle Pair Indexing. The Linear Combination of Views method of Ullman and Basri is employed as the projection model in the 3D experiments. 2004-10-20T20:23:39Z 2004-10-20T20:23:39Z 1993-01-01 AITR-1398 http://hdl.handle.net/1721.1/7046 en_US AITR-1398 11809727 bytes 6702525 bytes application/postscript application/pdf application/postscript application/pdf |
| spellingShingle | Wells, William M. III Statistical Object Recognition |
| title | Statistical Object Recognition |
| title_full | Statistical Object Recognition |
| title_fullStr | Statistical Object Recognition |
| title_full_unstemmed | Statistical Object Recognition |
| title_short | Statistical Object Recognition |
| title_sort | statistical object recognition |
| url | http://hdl.handle.net/1721.1/7046 |
| work_keys_str_mv | AT wellswilliammiii statisticalobjectrecognition |