Robust algorithms for model-based object recognition and localization
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2005
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| Online Access: | http://hdl.handle.net/1721.1/9440 |
| _version_ | 1811084051953483776 |
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| author | Bazzi, Louay Mohamad Jamil, 1974- |
| author2 | Sanjoy K. Mitter. |
| author_facet | Sanjoy K. Mitter. Bazzi, Louay Mohamad Jamil, 1974- |
| author_sort | Bazzi, Louay Mohamad Jamil, 1974- |
| collection | MIT |
| description | Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999. |
| first_indexed | 2024-09-23T12:43:54Z |
| format | Thesis |
| id | mit-1721.1/9440 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T12:43:54Z |
| publishDate | 2005 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/94402020-03-31T14:33:55Z Robust algorithms for model-based object recognition and localization Bazzi, Louay Mohamad Jamil, 1974- Sanjoy K. Mitter. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Electrical Engineering and Computer Science Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999. Includes bibliographical references (p. 86-87). We consider the problem of model-based object recognition and localization in the presence of noise, spurious features, and occlusion. We address the case where the model is allowed to be transformed by elements in a given space of allowable transformations. Known algorithms for the problem either treat noise very accurately in an unacceptable worst case running time, or may have unreliable output when noise is allowed. We introduce the idea of tolerance which measures the robustness of a recognition and localization method when noise is allowed. We present a collection of algorithms for the problem, each achieving a different degree of tolerance. The main result is a localization algorithm that achieves any desired tolerance in a relatively low order worst case asymptotic running time. The time constant of the algorithm depends on the ratio of the noise bound over the given tolerance bound. The solution we provide is general enough to handle different cases of allowable transformations, such as planar affine transformations, and scaled rigid motions in arbitrary dimensions. by Louay Mohamad Jamil Bazzi. S.M. 2005-08-22T18:23:15Z 2005-08-22T18:23:15Z 1999 1999 Thesis http://hdl.handle.net/1721.1/9440 43412515 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 87 leaves 4963975 bytes 4963731 bytes application/pdf application/pdf application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science Bazzi, Louay Mohamad Jamil, 1974- Robust algorithms for model-based object recognition and localization |
| title | Robust algorithms for model-based object recognition and localization |
| title_full | Robust algorithms for model-based object recognition and localization |
| title_fullStr | Robust algorithms for model-based object recognition and localization |
| title_full_unstemmed | Robust algorithms for model-based object recognition and localization |
| title_short | Robust algorithms for model-based object recognition and localization |
| title_sort | robust algorithms for model based object recognition and localization |
| topic | Electrical Engineering and Computer Science |
| url | http://hdl.handle.net/1721.1/9440 |
| work_keys_str_mv | AT bazzilouaymohamadjamil1974 robustalgorithmsformodelbasedobjectrecognitionandlocalization |