On computational Gestalt detection thresholds
Resumen:
The aim of this paper is to show some recent developments of computational Gestalt theory, as pioneered by Desolneux, Moisan and Morel. The new results allow to predict much more accurately the detection thresholds. This step is unavoidable if one wants to analyze visual detection thresholds in the light of computational Gestalt theory. The paper first recalls the main elements of computational Gestalt theory. It points out a precision issue in this theory, essentially due to the use of discrete probability distributions. It then proposes to overcome this issue by using continuous probability distributions and illustrates it on the meaningful alignment detector of Desolneux et al.
| 2009 | |
|
Computational Gestalt theory NFA A contrario detection Detection threshold Binomial distribution |
|
| Español | |
| Universidad de la República | |
| COLIBRI | |
| https://hdl.handle.net/20.500.12008/38667 | |
| Acceso abierto | |
| Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
| _version_ | 1807522934084861952 |
|---|---|
| author | Grompone von Gioi, Rafael |
| author2 | Jakubowicz, Jérémie |
| author2_role | author |
| author_facet | Grompone von Gioi, Rafael Jakubowicz, Jérémie |
| author_role | author |
| bitstream.checksum.fl_str_mv | 7f2e2c17ef6585de66da58d1bfa8b5e1 9833653f73f7853880c94a6fead477b1 4afdbb8c545fd630ea7db775da747b2f 9da0b6dfac957114c6a7714714b86306 |
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| collection | COLIBRI |
| dc.creator.none.fl_str_mv | Grompone von Gioi, Rafael Jakubowicz, Jérémie |
| dc.date.accessioned.none.fl_str_mv | 2023-08-01T20:33:15Z |
| dc.date.available.none.fl_str_mv | 2023-08-01T20:33:15Z |
| dc.date.issued.es.fl_str_mv | 2009 |
| dc.date.submitted.es.fl_str_mv | 20230801 |
| dc.description.abstract.none.fl_txt_mv | The aim of this paper is to show some recent developments of computational Gestalt theory, as pioneered by Desolneux, Moisan and Morel. The new results allow to predict much more accurately the detection thresholds. This step is unavoidable if one wants to analyze visual detection thresholds in the light of computational Gestalt theory. The paper first recalls the main elements of computational Gestalt theory. It points out a precision issue in this theory, essentially due to the use of discrete probability distributions. It then proposes to overcome this issue by using continuous probability distributions and illustrates it on the meaningful alignment detector of Desolneux et al. |
| dc.identifier.citation.es.fl_str_mv | Grompone von Gioi, R, Jakubowicz, J. “On computational Gestalt detection thresholds”. Journal of Physiology, 2009, v. 103, no. 1-2. |
| dc.identifier.uri.none.fl_str_mv | https://hdl.handle.net/20.500.12008/38667 |
| dc.language.iso.none.fl_str_mv | es spa |
| dc.publisher.es.fl_str_mv | Elsevier |
| dc.relation.ispartof.es.fl_str_mv | Journal of Physiology – Paris, 2009, v. 103, no. 1-2 |
| dc.rights.license.none.fl_str_mv | Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
| 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.es.fl_str_mv | Computational Gestalt theory NFA A contrario detection Detection threshold Binomial distribution |
| dc.title.none.fl_str_mv | On computational Gestalt detection thresholds |
| dc.type.es.fl_str_mv | Artículo |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/article |
| dc.type.version.none.fl_str_mv | info:eu-repo/semantics/publishedVersion |
| description | The aim of this paper is to show some recent developments of computational Gestalt theory, as pioneered by Desolneux, Moisan and Morel. The new results allow to predict much more accurately the detection thresholds. This step is unavoidable if one wants to analyze visual detection thresholds in the light of computational Gestalt theory. The paper first recalls the main elements of computational Gestalt theory. It points out a precision issue in this theory, essentially due to the use of discrete probability distributions. It then proposes to overcome this issue by using continuous probability distributions and illustrates it on the meaningful alignment detector of Desolneux et al. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | COLIBRI_053ea18d19e6e49b6cf124c740e444c0 |
| identifier_str_mv | Grompone von Gioi, R, Jakubowicz, J. “On computational Gestalt detection thresholds”. Journal of Physiology, 2009, v. 103, no. 1-2. |
| instacron_str | Universidad de la República |
| institution | Universidad de la República |
| instname_str | Universidad de la República |
| language | spa |
| language_invalid_str_mv | es |
| network_acronym_str | COLIBRI |
| network_name_str | COLIBRI |
| oai_identifier_str | oai:colibri.udelar.edu.uy:20.500.12008/38667 |
| publishDate | 2009 |
| 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 4.0) |
| spelling | 2023-08-01T20:33:15Z2023-08-01T20:33:15Z200920230801Grompone von Gioi, R, Jakubowicz, J. “On computational Gestalt detection thresholds”. Journal of Physiology, 2009, v. 103, no. 1-2.https://hdl.handle.net/20.500.12008/38667The aim of this paper is to show some recent developments of computational Gestalt theory, as pioneered by Desolneux, Moisan and Morel. The new results allow to predict much more accurately the detection thresholds. This step is unavoidable if one wants to analyze visual detection thresholds in the light of computational Gestalt theory. The paper first recalls the main elements of computational Gestalt theory. It points out a precision issue in this theory, essentially due to the use of discrete probability distributions. It then proposes to overcome this issue by using continuous probability distributions and illustrates it on the meaningful alignment detector of Desolneux et al.Made available in DSpace on 2023-08-01T20:33:15Z (GMT). No. of bitstreams: 4 license_text: 21936 bytes, checksum: 9833653f73f7853880c94a6fead477b1 (MD5) license_url: 49 bytes, checksum: 4afdbb8c545fd630ea7db775da747b2f (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) license.txt: 4194 bytes, checksum: 7f2e2c17ef6585de66da58d1bfa8b5e1 (MD5) Previous issue date: 2009esspaElsevierJournal of Physiology – Paris, 2009, v. 103, no. 1-2Las 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 4.0)Computational Gestalt theoryNFAA contrario detectionDetection thresholdBinomial distributionOn computational Gestalt detection thresholdsArtículoinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionreponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaGrompone von Gioi, RafaelJakubowicz, 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- Universidad de la Repúblicafalse |
| spellingShingle | On computational Gestalt detection thresholds Grompone von Gioi, Rafael Computational Gestalt theory NFA A contrario detection Detection threshold Binomial distribution |
| status_str | publishedVersion |
| title | On computational Gestalt detection thresholds |
| title_full | On computational Gestalt detection thresholds |
| title_fullStr | On computational Gestalt detection thresholds |
| title_full_unstemmed | On computational Gestalt detection thresholds |
| title_short | On computational Gestalt detection thresholds |
| title_sort | On computational Gestalt detection thresholds |
| topic | Computational Gestalt theory NFA A contrario detection Detection threshold Binomial distribution |
| url | https://hdl.handle.net/20.500.12008/38667 |
