Modeling the spatial layout of images beyond spatial pyramids
- Autores
- Sanchez, Jorge Adrian; Perronnin, Florent; de Campos, Teófilo
- Año de publicación
- 2012
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Several state-of-the-art image representations consist in averaging local statistics computed from patch-level descriptors. It has been shown by Boureau et al. that such average statistics suffer from two sources of variance. The first one comes from the fact that a finite set of local statistics are averaged. The second one is due to the variation in the proportion of object-dependent information between different images of the same class. For the problem of object classification, these sources of variance affect negatively the accuracy since they increase the overlap between class-conditional probabilities. Our goal is to include information about the spatial layout of images in image signatures based on average statistics. We show that the traditional approach to including the spatial layout ? the spatial pyramid (SP) ? increases the first source of variance while only weakly reducing the second one. We therefore propose two complementary approaches to account for the spatial layout which are compatible with our goal of variance reduction. The first one models the spatial layout in an image-independent manner (as is the case of the SP) while the second one adapts to the image content. A significant benefit of these approaches with respect to the SP is that they do not incur an increase of the image signature dimensionality. We show on PASCAL VOC 2007, 2008 and 2009 the benefits of our approach.
Fil: Sanchez, Jorge Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; Argentina
Fil: Perronnin, Florent. Xerox Research Centre Europe; Francia
Fil: de Campos, Teófilo. University of Surrey; Reino Unido - Materia
-
IMAGE REPRESENTATION
SPATIAL LAYOUT
IMAGE CATEGORIZATION
FISHER VECTORS
PASCAL VOC DATASET
SPATIAL PYRAMIDS - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/271744
Ver los metadatos del registro completo
id |
CONICETDig_3c7b03af4bc9d1cc88be001e689642cf |
---|---|
oai_identifier_str |
oai:ri.conicet.gov.ar:11336/271744 |
network_acronym_str |
CONICETDig |
repository_id_str |
3498 |
network_name_str |
CONICET Digital (CONICET) |
spelling |
Modeling the spatial layout of images beyond spatial pyramidsSanchez, Jorge AdrianPerronnin, Florentde Campos, TeófiloIMAGE REPRESENTATIONSPATIAL LAYOUTIMAGE CATEGORIZATIONFISHER VECTORSPASCAL VOC DATASETSPATIAL PYRAMIDShttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Several state-of-the-art image representations consist in averaging local statistics computed from patch-level descriptors. It has been shown by Boureau et al. that such average statistics suffer from two sources of variance. The first one comes from the fact that a finite set of local statistics are averaged. The second one is due to the variation in the proportion of object-dependent information between different images of the same class. For the problem of object classification, these sources of variance affect negatively the accuracy since they increase the overlap between class-conditional probabilities. Our goal is to include information about the spatial layout of images in image signatures based on average statistics. We show that the traditional approach to including the spatial layout ? the spatial pyramid (SP) ? increases the first source of variance while only weakly reducing the second one. We therefore propose two complementary approaches to account for the spatial layout which are compatible with our goal of variance reduction. The first one models the spatial layout in an image-independent manner (as is the case of the SP) while the second one adapts to the image content. A significant benefit of these approaches with respect to the SP is that they do not incur an increase of the image signature dimensionality. We show on PASCAL VOC 2007, 2008 and 2009 the benefits of our approach.Fil: Sanchez, Jorge Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; ArgentinaFil: Perronnin, Florent. Xerox Research Centre Europe; FranciaFil: de Campos, Teófilo. University of Surrey; Reino UnidoElsevier Science2012-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/271744Sanchez, Jorge Adrian; Perronnin, Florent; de Campos, Teófilo; Modeling the spatial layout of images beyond spatial pyramids; Elsevier Science; Pattern Recognition Letters; 33; 16; 12-2012; 2216-22230167-8655CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0167865512002413info:eu-repo/semantics/altIdentifier/doi/10.1016/j.patrec.2012.07.019info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:44:25Zoai:ri.conicet.gov.ar:11336/271744instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:44:25.716CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Modeling the spatial layout of images beyond spatial pyramids |
title |
Modeling the spatial layout of images beyond spatial pyramids |
spellingShingle |
Modeling the spatial layout of images beyond spatial pyramids Sanchez, Jorge Adrian IMAGE REPRESENTATION SPATIAL LAYOUT IMAGE CATEGORIZATION FISHER VECTORS PASCAL VOC DATASET SPATIAL PYRAMIDS |
title_short |
Modeling the spatial layout of images beyond spatial pyramids |
title_full |
Modeling the spatial layout of images beyond spatial pyramids |
title_fullStr |
Modeling the spatial layout of images beyond spatial pyramids |
title_full_unstemmed |
Modeling the spatial layout of images beyond spatial pyramids |
title_sort |
Modeling the spatial layout of images beyond spatial pyramids |
dc.creator.none.fl_str_mv |
Sanchez, Jorge Adrian Perronnin, Florent de Campos, Teófilo |
author |
Sanchez, Jorge Adrian |
author_facet |
Sanchez, Jorge Adrian Perronnin, Florent de Campos, Teófilo |
author_role |
author |
author2 |
Perronnin, Florent de Campos, Teófilo |
author2_role |
author author |
dc.subject.none.fl_str_mv |
IMAGE REPRESENTATION SPATIAL LAYOUT IMAGE CATEGORIZATION FISHER VECTORS PASCAL VOC DATASET SPATIAL PYRAMIDS |
topic |
IMAGE REPRESENTATION SPATIAL LAYOUT IMAGE CATEGORIZATION FISHER VECTORS PASCAL VOC DATASET SPATIAL PYRAMIDS |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.2 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
Several state-of-the-art image representations consist in averaging local statistics computed from patch-level descriptors. It has been shown by Boureau et al. that such average statistics suffer from two sources of variance. The first one comes from the fact that a finite set of local statistics are averaged. The second one is due to the variation in the proportion of object-dependent information between different images of the same class. For the problem of object classification, these sources of variance affect negatively the accuracy since they increase the overlap between class-conditional probabilities. Our goal is to include information about the spatial layout of images in image signatures based on average statistics. We show that the traditional approach to including the spatial layout ? the spatial pyramid (SP) ? increases the first source of variance while only weakly reducing the second one. We therefore propose two complementary approaches to account for the spatial layout which are compatible with our goal of variance reduction. The first one models the spatial layout in an image-independent manner (as is the case of the SP) while the second one adapts to the image content. A significant benefit of these approaches with respect to the SP is that they do not incur an increase of the image signature dimensionality. We show on PASCAL VOC 2007, 2008 and 2009 the benefits of our approach. Fil: Sanchez, Jorge Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; Argentina Fil: Perronnin, Florent. Xerox Research Centre Europe; Francia Fil: de Campos, Teófilo. University of Surrey; Reino Unido |
description |
Several state-of-the-art image representations consist in averaging local statistics computed from patch-level descriptors. It has been shown by Boureau et al. that such average statistics suffer from two sources of variance. The first one comes from the fact that a finite set of local statistics are averaged. The second one is due to the variation in the proportion of object-dependent information between different images of the same class. For the problem of object classification, these sources of variance affect negatively the accuracy since they increase the overlap between class-conditional probabilities. Our goal is to include information about the spatial layout of images in image signatures based on average statistics. We show that the traditional approach to including the spatial layout ? the spatial pyramid (SP) ? increases the first source of variance while only weakly reducing the second one. We therefore propose two complementary approaches to account for the spatial layout which are compatible with our goal of variance reduction. The first one models the spatial layout in an image-independent manner (as is the case of the SP) while the second one adapts to the image content. A significant benefit of these approaches with respect to the SP is that they do not incur an increase of the image signature dimensionality. We show on PASCAL VOC 2007, 2008 and 2009 the benefits of our approach. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-12 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/271744 Sanchez, Jorge Adrian; Perronnin, Florent; de Campos, Teófilo; Modeling the spatial layout of images beyond spatial pyramids; Elsevier Science; Pattern Recognition Letters; 33; 16; 12-2012; 2216-2223 0167-8655 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/271744 |
identifier_str_mv |
Sanchez, Jorge Adrian; Perronnin, Florent; de Campos, Teófilo; Modeling the spatial layout of images beyond spatial pyramids; Elsevier Science; Pattern Recognition Letters; 33; 16; 12-2012; 2216-2223 0167-8655 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0167865512002413 info:eu-repo/semantics/altIdentifier/doi/10.1016/j.patrec.2012.07.019 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier Science |
publisher.none.fl_str_mv |
Elsevier Science |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
reponame_str |
CONICET Digital (CONICET) |
collection |
CONICET Digital (CONICET) |
instname_str |
Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.name.fl_str_mv |
CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
_version_ |
1844613398046703616 |
score |
13.070432 |