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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPBW34M/3K2HFE8
Repositorysid.inpe.br/sibgrapi/2015/08.06.20.16
Last Update2015:08.06.20.16.39 (UTC) balbson@gmail.com
Metadata Repositorysid.inpe.br/sibgrapi/2015/08.06.20.16.39
Metadata Last Update2022:05.18.22.21.02 (UTC) administrator
Citation KeyMesquitaCampNasc:2015:MeObSu
TitleA Methodology for Obtaining Super-Resolution Images and Depth Maps from RGB-D Data
FormatOn-line
Year2015
Access Date2024, Apr. 26
Secondary TypeMaster's Work
Number of Files1
Size2803 KiB
2. Context
Author1 Mesquita, Daniel Balbino de
2 Campos, Mario Fernando Montenegro
3 Nascimento, Erickson Rangel do
Affiliation1 Universidade Federal de Minas Gerais
2 Universidade Federal de Minas Gerais
3 Universidade Federal de Minas Gerais
EditorSegundo, Maurício Pamplona
Faria, Fabio Augusto
e-Mail Addressbalbson@gmail.com
Conference NameConference on Graphics, Patterns and Images, 28 (SIBGRAPI)
Conference LocationSalvador, BA, Brazil
Date26-29 Aug. 2015
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeMaster's or Doctoral Work
History (UTC)2015-08-06 20:16:39 :: balbson@gmail.com -> administrator ::
2022-05-18 22:21:02 :: administrator -> :: 2015
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordssuper-resolution
convex optimization
RGB-D data
3D reconstruction
computer vision
AbstractThe emergence of low cost sensors capable of providing texture and depth information of a scene is enabling the deployment of several applications such as gesture and object recognition and three-dimensional reconstruction of environments. However, commercially available sensors output low resolution data, which may not be suitable when more detailed information is necessary. With the purpose of increasing data resolution, at the same time reducing noise and filling the holes in the depth maps, in this work we propose a method that combines depth fusion and image reconstruction in a super-resolution framework. By joining low-resolution intensity images and depth maps in an optimization process, our methodology creates new images and depth maps of higher resolution and, at the same time, minimizes issues related with the absence of information (holes) in the depth map. Our experiments show that the proposed approach has increased the resolution of the images and depth maps without significant spawning of artifacts. Considering three different evaluation metrics, our methodology outperformed other three techniques commonly used to increase the resolution of combined images and depth maps acquired with low resolution, commercially available sensors.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2015 > A Methodology for...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPBW34M/3K2HFE8
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3K2HFE8
Languageen
Target Filesibgrapi_2015_wtd_rgbd_superresolution_camera_ready.pdf
User Groupbalbson@gmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPBW34M/3K24PF8
Citing Item Listsid.inpe.br/sibgrapi/2015/08.03.22.49 5
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination doi edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume


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