Joint estimation of segmentation and structure from motion
We present a novel optimisation framework for the estimation of the multi-body motion segmentation and 3D reconstruction of a set of point trajectories in the presence of missing data. The proposed solution not only assigns the trajectories to the correct motion but it also solves for the 3D locatio...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2013 |
| País: | España |
| Institución: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10256/11544 |
| Acceso en línea: | http://hdl.handle.net/10256/11544 |
| Access Level: | acceso embargado |
| Palabra clave: | Imatges -- Processament Image processing Visió per ordinador Computer vision |
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Joint estimation of segmentation and structure from motionZappella, LucaDel Bue, AlessioLladó Bardera, XavierSalvi, JoaquimImatges -- ProcessamentImage processingVisió per ordinadorComputer visionWe present a novel optimisation framework for the estimation of the multi-body motion segmentation and 3D reconstruction of a set of point trajectories in the presence of missing data. The proposed solution not only assigns the trajectories to the correct motion but it also solves for the 3D location of multi-body shape and it fills the missing entries in the measurement matrix. Such a solution is based on two fundamental principles: each of the multi-body motions is controlled by a set of metric constraints that are given by the specific camera model, and the shape matrix that describes the multi-body 3D shape is generally sparse. We jointly include such constraints in a unique optimisation framework which, starting from an initial segmentation, iteratively enforces these set of constraints in three stages. First, metric constraints are used to estimate the 3D metric shape and to fill the missing entries according to an orthographic camera model. Then, wrongly segmented trajectories are detected by using sparse optimisation of the shape matrix. A final reclassification strategy assigns the detected points to the right motion or discards them as outliers. We provide experiments that show consistent improvements to previous approaches both on synthetic and real dataThis work has been supported by the Spanish Ministry of Science and Innovation projects CTM2011-29691-C02-02. L. Zappella was supported by the Catalan government scholarship 2009FI B1 00068ElsevierMinisterio de Ciencia e Innovación (Espanya)infoinfo2013info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10256/11544http://hdl.handle.net/10256/11544© Computer Vision and Image Understanding, 2013, vol. 117, núm. 2, p. 113-129Articles publicats (D-ATC)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)Inglésinfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.cviu.2012.09.004info:eu-repo/semantics/altIdentifier/issn/1077-3142info:eu-repo/grantAgreement/MICINN//CTM2011-29691-C02-02Tots els drets reservatsinfo:eu-repo/semantics/embargoedAccessoai:recercat.cat:10256/115442026-05-29T05:05:01Z |
| dc.title.none.fl_str_mv |
Joint estimation of segmentation and structure from motion |
| title |
Joint estimation of segmentation and structure from motion |
| spellingShingle |
Joint estimation of segmentation and structure from motion Zappella, Luca Imatges -- Processament Image processing Visió per ordinador Computer vision |
| title_short |
Joint estimation of segmentation and structure from motion |
| title_full |
Joint estimation of segmentation and structure from motion |
| title_fullStr |
Joint estimation of segmentation and structure from motion |
| title_full_unstemmed |
Joint estimation of segmentation and structure from motion |
| title_sort |
Joint estimation of segmentation and structure from motion |
| dc.creator.none.fl_str_mv |
Zappella, Luca Del Bue, Alessio Lladó Bardera, Xavier Salvi, Joaquim |
| author |
Zappella, Luca |
| author_facet |
Zappella, Luca Del Bue, Alessio Lladó Bardera, Xavier Salvi, Joaquim |
| author_role |
author |
| author2 |
Del Bue, Alessio Lladó Bardera, Xavier Salvi, Joaquim |
| author2_role |
author author author |
| dc.contributor.none.fl_str_mv |
Ministerio de Ciencia e Innovación (Espanya) |
| dc.subject.none.fl_str_mv |
Imatges -- Processament Image processing Visió per ordinador Computer vision |
| topic |
Imatges -- Processament Image processing Visió per ordinador Computer vision |
| description |
We present a novel optimisation framework for the estimation of the multi-body motion segmentation and 3D reconstruction of a set of point trajectories in the presence of missing data. The proposed solution not only assigns the trajectories to the correct motion but it also solves for the 3D location of multi-body shape and it fills the missing entries in the measurement matrix. Such a solution is based on two fundamental principles: each of the multi-body motions is controlled by a set of metric constraints that are given by the specific camera model, and the shape matrix that describes the multi-body 3D shape is generally sparse. We jointly include such constraints in a unique optimisation framework which, starting from an initial segmentation, iteratively enforces these set of constraints in three stages. First, metric constraints are used to estimate the 3D metric shape and to fill the missing entries according to an orthographic camera model. Then, wrongly segmented trajectories are detected by using sparse optimisation of the shape matrix. A final reclassification strategy assigns the detected points to the right motion or discards them as outliers. We provide experiments that show consistent improvements to previous approaches both on synthetic and real data |
| publishDate |
2013 |
| dc.date.none.fl_str_mv |
2013 info info |
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info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
http://hdl.handle.net/10256/11544 http://hdl.handle.net/10256/11544 |
| url |
http://hdl.handle.net/10256/11544 |
| dc.language.none.fl_str_mv |
Inglés |
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Inglés |
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info:eu-repo/semantics/altIdentifier/doi/10.1016/j.cviu.2012.09.004 info:eu-repo/semantics/altIdentifier/issn/1077-3142 info:eu-repo/grantAgreement/MICINN//CTM2011-29691-C02-02 |
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Tots els drets reservats info:eu-repo/semantics/embargoedAccess |
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Tots els drets reservats |
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embargoedAccess |
| dc.format.none.fl_str_mv |
application/pdf |
| dc.publisher.none.fl_str_mv |
Elsevier |
| publisher.none.fl_str_mv |
Elsevier |
| dc.source.none.fl_str_mv |
© Computer Vision and Image Understanding, 2013, vol. 117, núm. 2, p. 113-129 Articles publicats (D-ATC) reponame:Recercat. Dipósit de la Recerca de Catalunya instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
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Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
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Recercat. Dipósit de la Recerca de Catalunya |
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Recercat. Dipósit de la Recerca de Catalunya |
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1869412851961036800 |
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15.81155 |