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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Identifier8JMKD3MGPEW34M/47M99TB
Repositorysid.inpe.br/sibgrapi/2022/09.24.23.21
Last Update2022:09.24.23.21.45 (UTC) lmarcos@dca.ufrn.br
Metadata Repositorysid.inpe.br/sibgrapi/2022/09.24.23.21.45
Metadata Last Update2023:05.23.04.20.43 (UTC) administrator
DOI10.1109/SIBGRAPI55357.2022.9991789
Citation KeyOrtiz-FernandezSilvGonc:2022:ErAcEs
TitleError Accuracy Estimation of 3D Reconstruction and 3D Camera Pose from RGB-D Data
FormatOn-line
Year2022
Access Date2024, May 03
Number of Files1
Size2435 KiB
2. Context
Author1 Ortiz-Fernandez, Luis Enrique
2 da Silva, Bruno Marques Ferreira
3 Goncalves, Luiz Marcos Garcia
Affiliation1 Universidade Federal do Rio Grande do Norte
2 Universidade Federal do Rio Grande do Norte
3 Universidade Federal do Rio Grande do Norte
e-Mail Addressleofaf@gmail.com
Conference NameConference on Graphics, Patterns and Images, 35 (SIBGRAPI)
Conference LocationNatal, RN
Date24-27 Oct. 2022
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2022-09-24 23:21:45 :: lmarcos@dca.ufrn.br -> administrator ::
2023-05-23 04:20:43 :: administrator -> :: 2022
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordserrors prediction
camera positioning
3D reconstruction
RGB-D cameras
AbstractWe propose an approach to predict accuracy for three-dimensional reconstruction and camera pose using a generic RGB-D camera on a robotic platform. We initially create a ground truth of 3D points and camera poses using a set of smart markers that we specifically devised and constructed for our approach. Then, we compute actual errors and their accuracy during the motion of our mobile robotic platform. The modeling of the error is then provided, which is used as input to a deep multi-layer perceptron in order to estimate accuracy as a function of the camera's distance, velocity, and vibration of the vision system. The network outputs are the root mean squared errors for the 3D reconstruction and the relative pose errors for the camera. Experimental results show that this approach has a prediction accuracy of 1 % for the 3D reconstruction and 2.5 % for camera poses, which shows a better performance in comparison with state-of-the-art methods.
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zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/47M99TB
Languageen
Target FileOrtizFernandezSIBGRAPI2022 (7).pdf
User Grouplmarcos@dca.ufrn.br
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/495MHJ8
Citing Item Listsid.inpe.br/sibgrapi/2023/05.19.12.10 5
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage edition editor electronicmailaddress group holdercode isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume


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