Unsupervised thresholds for shape matching
Resumen:
Shape recognition systems usually order a fixed number of best matches to each query, but do not address or answer the two following questions: Is a query shape in a given database? How can we be sure that a match is correct? This communication deals with these two key points. A database being given, with each shape S and each distance /spl delta/, we associate its number of false alarms NFA(S, /spl delta/), namely the expectation of the number of shapes at distance /spl delta/ in the database. Assume that NFA(S, /spl delta/) is very small with respect to 1, and that a shape S' is found at distance /spl delta/ from S in the database. This match could not occur just by chance and is therefore a meaningful detection. Its explanation is usually the common origin of both shapes. Experimental evidence will show that NFA(S, /spl delta/) can be predicted accurately.
| 2003 | |
|
Visual databases Image matching Computer vision |
|
| Inglés | |
| Universidad de la República | |
| COLIBRI | |
| https://hdl.handle.net/20.500.12008/21252 | |
| Acceso abierto | |
| Licencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC - By-NC-ND) |
| _version_ | 1807522894956199936 |
|---|---|
| author | Musé, Pablo |
| author2 | Sur, Frederic Cao, Frederic Gousseau, Yann |
| author2_role | author author author |
| author_facet | Musé, Pablo Sur, Frederic Cao, Frederic Gousseau, Yann |
| author_role | author |
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| bitstream.checksumAlgorithm.fl_str_mv | MD5 MD5 MD5 MD5 MD5 |
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| collection | COLIBRI |
| dc.creator.none.fl_str_mv | Musé, Pablo Sur, Frederic Cao, Frederic Gousseau, Yann |
| dc.date.accessioned.none.fl_str_mv | 2019-07-03T16:36:13Z |
| dc.date.available.none.fl_str_mv | 2019-07-03T16:36:13Z |
| dc.date.issued.es.fl_str_mv | 2003 |
| dc.date.submitted.es.fl_str_mv | 20190703 |
| dc.description.abstract.none.fl_txt_mv | Shape recognition systems usually order a fixed number of best matches to each query, but do not address or answer the two following questions: Is a query shape in a given database? How can we be sure that a match is correct? This communication deals with these two key points. A database being given, with each shape S and each distance /spl delta/, we associate its number of false alarms NFA(S, /spl delta/), namely the expectation of the number of shapes at distance /spl delta/ in the database. Assume that NFA(S, /spl delta/) is very small with respect to 1, and that a shape S' is found at distance /spl delta/ from S in the database. This match could not occur just by chance and is therefore a meaningful detection. Its explanation is usually the common origin of both shapes. Experimental evidence will show that NFA(S, /spl delta/) can be predicted accurately. |
| dc.identifier.citation.es.fl_str_mv | Musé, P, Sur, Frederic, Cao, Frederic, Gousseau, Yann. Unsupervised thresholds for shape matching [Preprint] Publicado en International Conference on Image Processing, 2003. Proceedings. Doi 10.1109/ICIP.2003.1246763 |
| dc.identifier.uri.none.fl_str_mv | https://hdl.handle.net/20.500.12008/21252 |
| dc.language.iso.none.fl_str_mv | en eng |
| dc.rights.license.none.fl_str_mv | Licencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC - By-NC-ND) |
| dc.rights.none.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.source.none.fl_str_mv | reponame:COLIBRI instname:Universidad de la República instacron:Universidad de la República |
| dc.subject.en.fl_str_mv | Visual databases Image matching Computer vision |
| dc.title.none.fl_str_mv | Unsupervised thresholds for shape matching |
| dc.type.en.fl_str_mv | Preprint |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/preprint |
| dc.type.version.none.fl_str_mv | info:eu-repo/semantics/submittedVersion |
| description | Shape recognition systems usually order a fixed number of best matches to each query, but do not address or answer the two following questions: Is a query shape in a given database? How can we be sure that a match is correct? This communication deals with these two key points. A database being given, with each shape S and each distance /spl delta/, we associate its number of false alarms NFA(S, /spl delta/), namely the expectation of the number of shapes at distance /spl delta/ in the database. Assume that NFA(S, /spl delta/) is very small with respect to 1, and that a shape S' is found at distance /spl delta/ from S in the database. This match could not occur just by chance and is therefore a meaningful detection. Its explanation is usually the common origin of both shapes. Experimental evidence will show that NFA(S, /spl delta/) can be predicted accurately. |
| eu_rights_str_mv | openAccess |
| format | preprint |
| id | COLIBRI_daa6959d60206f27bc7e7790b24f8932 |
| identifier_str_mv | Musé, P, Sur, Frederic, Cao, Frederic, Gousseau, Yann. Unsupervised thresholds for shape matching [Preprint] Publicado en International Conference on Image Processing, 2003. Proceedings. Doi 10.1109/ICIP.2003.1246763 |
| instacron_str | Universidad de la República |
| institution | Universidad de la República |
| instname_str | Universidad de la República |
| language | eng |
| language_invalid_str_mv | en |
| network_acronym_str | COLIBRI |
| network_name_str | COLIBRI |
| oai_identifier_str | oai:colibri.udelar.edu.uy:20.500.12008/21252 |
| publishDate | 2003 |
| reponame_str | COLIBRI |
| repository.mail.fl_str_mv | mabel.seroubian@seciu.edu.uy |
| repository.name.fl_str_mv | COLIBRI - Universidad de la República |
| repository_id_str | 4771 |
| rights_invalid_str_mv | Licencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC - By-NC-ND) |
| spelling | 2019-07-03T16:36:13Z2019-07-03T16:36:13Z200320190703Musé, P, Sur, Frederic, Cao, Frederic, Gousseau, Yann. Unsupervised thresholds for shape matching [Preprint] Publicado en International Conference on Image Processing, 2003. Proceedings. Doi 10.1109/ICIP.2003.1246763https://hdl.handle.net/20.500.12008/21252Shape recognition systems usually order a fixed number of best matches to each query, but do not address or answer the two following questions: Is a query shape in a given database? How can we be sure that a match is correct? This communication deals with these two key points. A database being given, with each shape S and each distance /spl delta/, we associate its number of false alarms NFA(S, /spl delta/), namely the expectation of the number of shapes at distance /spl delta/ in the database. Assume that NFA(S, /spl delta/) is very small with respect to 1, and that a shape S' is found at distance /spl delta/ from S in the database. This match could not occur just by chance and is therefore a meaningful detection. Its explanation is usually the common origin of both shapes. Experimental evidence will show that NFA(S, /spl delta/) can be predicted accurately.Made available in DSpace on 2019-07-03T16:36:13Z (GMT). No. of bitstreams: 5 unsupervised-tresholds.pdf: 364801 bytes, checksum: 73b2621378a0a5b1d5bf38f899e2de87 (MD5) license_text: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) license_url: 49 bytes, checksum: 4afdbb8c545fd630ea7db775da747b2f (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) license.txt: 4267 bytes, checksum: 6429389a7df7277b72b7924fdc7d47a9 (MD5) Previous issue date: 2003enengLas obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad De La República. (Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)info:eu-repo/semantics/openAccessLicencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC - By-NC-ND)Visual databasesImage matchingComputer visionUnsupervised thresholds for shape matchingPreprintinfo:eu-repo/semantics/preprintinfo:eu-repo/semantics/submittedVersionreponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaMusé, PabloSur, FredericCao, FredericGousseau, 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- Universidad de la Repúblicafalse |
| spellingShingle | Unsupervised thresholds for shape matching Musé, Pablo Visual databases Image matching Computer vision |
| status_str | submittedVersion |
| title | Unsupervised thresholds for shape matching |
| title_full | Unsupervised thresholds for shape matching |
| title_fullStr | Unsupervised thresholds for shape matching |
| title_full_unstemmed | Unsupervised thresholds for shape matching |
| title_short | Unsupervised thresholds for shape matching |
| title_sort | Unsupervised thresholds for shape matching |
| topic | Visual databases Image matching Computer vision |
| url | https://hdl.handle.net/20.500.12008/21252 |
