Loading…

A Quadrifocal Tensor SFM Photogrammetry Positioning and Calibration Technique for HOFS Aerial Sensors

Nowadays, the integration between photogrammetry and structure from motion (SFM) has become much closer, and many attempts have been made to combine the two approaches to realize the positioning, calibration, and 3D reconstruction of a large number of images. For the positioning and calibration of h...

Full description

Saved in:
Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2022-08, Vol.14 (15), p.3521
Main Authors: Wang, Tao, Zhang, Yan, Zhang, Yongsheng, Yu, Ying, Li, Lei, Liu, Shaocong, Zhao, Xiang, Zhang, Zhenchao, Wang, Longhui
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites cdi_FETCH-LOGICAL-c320t-103109a9e32cee6022d598b55f3c1f8bae308654d6d70873b36e68ab21c92d723
container_end_page
container_issue 15
container_start_page 3521
container_title Remote sensing (Basel, Switzerland)
container_volume 14
creator Wang, Tao
Zhang, Yan
Zhang, Yongsheng
Yu, Ying
Li, Lei
Liu, Shaocong
Zhao, Xiang
Zhang, Zhenchao
Wang, Longhui
description Nowadays, the integration between photogrammetry and structure from motion (SFM) has become much closer, and many attempts have been made to combine the two approaches to realize the positioning, calibration, and 3D reconstruction of a large number of images. For the positioning and calibration of high oblique frame sweep (HOFS) aerial cameras, a quadrifocal tensor SFM photogrammetry technique is proposed to resolve the positioning and calibration task of such cameras. It adopts the quadrifocal tensor idea into the OpenMVG SFM pipeline to solve the complexity problem caused by the small single-viewing imaging area and the high image overlapping ratio. It also integrates the photogrammetry iteration idea into the OpenMVG SFM pipeline to enhance the positioning and calibration accuracy, which includes a coarse to fine three-stage Bundle Adjustment (BA) processing approach. In this paper, the overall workflow of the proposed technique was first introduced in detail, from feature extraction and image matching, relative rotation and translation estimation, global rotation and translation estimation, and the quadrifocal tensor model construction to the three-stage BA process and calibration. Then, experiments were carried out in the Zhengzhou area, implementing four types of adjustment methods. The results suggest that the proposed quadrifocal tensor SFM photogrammetry is suitable for large tilt frame sweep camera positioning and calibration without prior information on detailed camera intrinsic parameters and structure. The modifications made to the OpenMVG SFM pipeline enhanced the precision of image positioning and calibration and provided the precision level of professional photogrammetry software.
doi_str_mv 10.3390/rs14153521
format article
fullrecord <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_ecfa40d993364d099b234435a9add93f</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_ecfa40d993364d099b234435a9add93f</doaj_id><sourcerecordid>2700764760</sourcerecordid><originalsourceid>FETCH-LOGICAL-c320t-103109a9e32cee6022d598b55f3c1f8bae308654d6d70873b36e68ab21c92d723</originalsourceid><addsrcrecordid>eNpNkU1LAzEQhhdRUGov_oKAN6E6yWQ_cizF2oKiUj2H2SRbU9qNJttD_73bVtS5zDDM-8wMb5ZdcbhFVHAXE5c8x1zwk-xCQClGUihx-q8-z4YpraAPRK5AXmRuzF63ZKNvgqE1e3NtCpEtpk_s5SN0YRlps3Fd3LGXkHznQ-vbJaPWsgmtfR1p3-pV5qP1X1vHml48e54u2NhF3_MWB166zM4aWic3_MmD7H16_zaZjR6fH-aT8ePIoIBuxAE5KFIOhXGuACFsrqo6zxs0vKlqcghVkUtb2BKqEmssXFFRLbhRwpYCB9n8yLWBVvoz-g3FnQ7k9aER4lJT7LxZO-1MQxKsUoiFtKBULVBKzEmRtQqbnnV9ZH3G0L-WOr0K29j252tRApSFLAvop26OUyaGlKJrfrdy0HtX9J8r-A2cpX2e</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2700764760</pqid></control><display><type>article</type><title>A Quadrifocal Tensor SFM Photogrammetry Positioning and Calibration Technique for HOFS Aerial Sensors</title><source>Publicly Available Content Database</source><creator>Wang, Tao ; Zhang, Yan ; Zhang, Yongsheng ; Yu, Ying ; Li, Lei ; Liu, Shaocong ; Zhao, Xiang ; Zhang, Zhenchao ; Wang, Longhui</creator><creatorcontrib>Wang, Tao ; Zhang, Yan ; Zhang, Yongsheng ; Yu, Ying ; Li, Lei ; Liu, Shaocong ; Zhao, Xiang ; Zhang, Zhenchao ; Wang, Longhui</creatorcontrib><description>Nowadays, the integration between photogrammetry and structure from motion (SFM) has become much closer, and many attempts have been made to combine the two approaches to realize the positioning, calibration, and 3D reconstruction of a large number of images. For the positioning and calibration of high oblique frame sweep (HOFS) aerial cameras, a quadrifocal tensor SFM photogrammetry technique is proposed to resolve the positioning and calibration task of such cameras. It adopts the quadrifocal tensor idea into the OpenMVG SFM pipeline to solve the complexity problem caused by the small single-viewing imaging area and the high image overlapping ratio. It also integrates the photogrammetry iteration idea into the OpenMVG SFM pipeline to enhance the positioning and calibration accuracy, which includes a coarse to fine three-stage Bundle Adjustment (BA) processing approach. In this paper, the overall workflow of the proposed technique was first introduced in detail, from feature extraction and image matching, relative rotation and translation estimation, global rotation and translation estimation, and the quadrifocal tensor model construction to the three-stage BA process and calibration. Then, experiments were carried out in the Zhengzhou area, implementing four types of adjustment methods. The results suggest that the proposed quadrifocal tensor SFM photogrammetry is suitable for large tilt frame sweep camera positioning and calibration without prior information on detailed camera intrinsic parameters and structure. The modifications made to the OpenMVG SFM pipeline enhanced the precision of image positioning and calibration and provided the precision level of professional photogrammetry software.</description><identifier>ISSN: 2072-4292</identifier><identifier>EISSN: 2072-4292</identifier><identifier>DOI: 10.3390/rs14153521</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>a quadrifocal tensor ; Accuracy ; Bundle adjustment ; Calibration ; Cameras ; Datasets ; Digital cameras ; Feature extraction ; frame sweep aerial sensor ; Image enhancement ; Image reconstruction ; Iterative methods ; Motion perception ; oblique photogrammetry ; Parameter modification ; Photogrammetry ; Photography ; Remote sensing ; Rotation ; Semantics ; SFM photogrammetry ; Software ; Tensors ; Translation ; VisionMap A3 edge sensor ; Workflow</subject><ispartof>Remote sensing (Basel, Switzerland), 2022-08, Vol.14 (15), p.3521</ispartof><rights>2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c320t-103109a9e32cee6022d598b55f3c1f8bae308654d6d70873b36e68ab21c92d723</cites><orcidid>0000-0003-1062-2017 ; 0000-0003-4300-2607 ; 0000-0002-2405-2038</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2700764760/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2700764760?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25753,27924,27925,37012,44590,75126</link.rule.ids></links><search><creatorcontrib>Wang, Tao</creatorcontrib><creatorcontrib>Zhang, Yan</creatorcontrib><creatorcontrib>Zhang, Yongsheng</creatorcontrib><creatorcontrib>Yu, Ying</creatorcontrib><creatorcontrib>Li, Lei</creatorcontrib><creatorcontrib>Liu, Shaocong</creatorcontrib><creatorcontrib>Zhao, Xiang</creatorcontrib><creatorcontrib>Zhang, Zhenchao</creatorcontrib><creatorcontrib>Wang, Longhui</creatorcontrib><title>A Quadrifocal Tensor SFM Photogrammetry Positioning and Calibration Technique for HOFS Aerial Sensors</title><title>Remote sensing (Basel, Switzerland)</title><description>Nowadays, the integration between photogrammetry and structure from motion (SFM) has become much closer, and many attempts have been made to combine the two approaches to realize the positioning, calibration, and 3D reconstruction of a large number of images. For the positioning and calibration of high oblique frame sweep (HOFS) aerial cameras, a quadrifocal tensor SFM photogrammetry technique is proposed to resolve the positioning and calibration task of such cameras. It adopts the quadrifocal tensor idea into the OpenMVG SFM pipeline to solve the complexity problem caused by the small single-viewing imaging area and the high image overlapping ratio. It also integrates the photogrammetry iteration idea into the OpenMVG SFM pipeline to enhance the positioning and calibration accuracy, which includes a coarse to fine three-stage Bundle Adjustment (BA) processing approach. In this paper, the overall workflow of the proposed technique was first introduced in detail, from feature extraction and image matching, relative rotation and translation estimation, global rotation and translation estimation, and the quadrifocal tensor model construction to the three-stage BA process and calibration. Then, experiments were carried out in the Zhengzhou area, implementing four types of adjustment methods. The results suggest that the proposed quadrifocal tensor SFM photogrammetry is suitable for large tilt frame sweep camera positioning and calibration without prior information on detailed camera intrinsic parameters and structure. The modifications made to the OpenMVG SFM pipeline enhanced the precision of image positioning and calibration and provided the precision level of professional photogrammetry software.</description><subject>a quadrifocal tensor</subject><subject>Accuracy</subject><subject>Bundle adjustment</subject><subject>Calibration</subject><subject>Cameras</subject><subject>Datasets</subject><subject>Digital cameras</subject><subject>Feature extraction</subject><subject>frame sweep aerial sensor</subject><subject>Image enhancement</subject><subject>Image reconstruction</subject><subject>Iterative methods</subject><subject>Motion perception</subject><subject>oblique photogrammetry</subject><subject>Parameter modification</subject><subject>Photogrammetry</subject><subject>Photography</subject><subject>Remote sensing</subject><subject>Rotation</subject><subject>Semantics</subject><subject>SFM photogrammetry</subject><subject>Software</subject><subject>Tensors</subject><subject>Translation</subject><subject>VisionMap A3 edge sensor</subject><subject>Workflow</subject><issn>2072-4292</issn><issn>2072-4292</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpNkU1LAzEQhhdRUGov_oKAN6E6yWQ_cizF2oKiUj2H2SRbU9qNJttD_73bVtS5zDDM-8wMb5ZdcbhFVHAXE5c8x1zwk-xCQClGUihx-q8-z4YpraAPRK5AXmRuzF63ZKNvgqE1e3NtCpEtpk_s5SN0YRlps3Fd3LGXkHznQ-vbJaPWsgmtfR1p3-pV5qP1X1vHml48e54u2NhF3_MWB166zM4aWic3_MmD7H16_zaZjR6fH-aT8ePIoIBuxAE5KFIOhXGuACFsrqo6zxs0vKlqcghVkUtb2BKqEmssXFFRLbhRwpYCB9n8yLWBVvoz-g3FnQ7k9aER4lJT7LxZO-1MQxKsUoiFtKBULVBKzEmRtQqbnnV9ZH3G0L-WOr0K29j252tRApSFLAvop26OUyaGlKJrfrdy0HtX9J8r-A2cpX2e</recordid><startdate>20220801</startdate><enddate>20220801</enddate><creator>Wang, Tao</creator><creator>Zhang, Yan</creator><creator>Zhang, Yongsheng</creator><creator>Yu, Ying</creator><creator>Li, Lei</creator><creator>Liu, Shaocong</creator><creator>Zhao, Xiang</creator><creator>Zhang, Zhenchao</creator><creator>Wang, Longhui</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7QR</scope><scope>7SC</scope><scope>7SE</scope><scope>7SN</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>JQ2</scope><scope>KR7</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PCBAR</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-1062-2017</orcidid><orcidid>https://orcid.org/0000-0003-4300-2607</orcidid><orcidid>https://orcid.org/0000-0002-2405-2038</orcidid></search><sort><creationdate>20220801</creationdate><title>A Quadrifocal Tensor SFM Photogrammetry Positioning and Calibration Technique for HOFS Aerial Sensors</title><author>Wang, Tao ; Zhang, Yan ; Zhang, Yongsheng ; Yu, Ying ; Li, Lei ; Liu, Shaocong ; Zhao, Xiang ; Zhang, Zhenchao ; Wang, Longhui</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c320t-103109a9e32cee6022d598b55f3c1f8bae308654d6d70873b36e68ab21c92d723</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>a quadrifocal tensor</topic><topic>Accuracy</topic><topic>Bundle adjustment</topic><topic>Calibration</topic><topic>Cameras</topic><topic>Datasets</topic><topic>Digital cameras</topic><topic>Feature extraction</topic><topic>frame sweep aerial sensor</topic><topic>Image enhancement</topic><topic>Image reconstruction</topic><topic>Iterative methods</topic><topic>Motion perception</topic><topic>oblique photogrammetry</topic><topic>Parameter modification</topic><topic>Photogrammetry</topic><topic>Photography</topic><topic>Remote sensing</topic><topic>Rotation</topic><topic>Semantics</topic><topic>SFM photogrammetry</topic><topic>Software</topic><topic>Tensors</topic><topic>Translation</topic><topic>VisionMap A3 edge sensor</topic><topic>Workflow</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Tao</creatorcontrib><creatorcontrib>Zhang, Yan</creatorcontrib><creatorcontrib>Zhang, Yongsheng</creatorcontrib><creatorcontrib>Yu, Ying</creatorcontrib><creatorcontrib>Li, Lei</creatorcontrib><creatorcontrib>Liu, Shaocong</creatorcontrib><creatorcontrib>Zhao, Xiang</creatorcontrib><creatorcontrib>Zhang, Zhenchao</creatorcontrib><creatorcontrib>Wang, Longhui</creatorcontrib><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Ecology Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical &amp; Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric &amp; Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ANTE: Abstracts in New Technology &amp; Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>SciTech Premium Collection</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Engineering Database</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Earth, Atmospheric &amp; Aquatic Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>Directory of Open Access Journals</collection><jtitle>Remote sensing (Basel, Switzerland)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Tao</au><au>Zhang, Yan</au><au>Zhang, Yongsheng</au><au>Yu, Ying</au><au>Li, Lei</au><au>Liu, Shaocong</au><au>Zhao, Xiang</au><au>Zhang, Zhenchao</au><au>Wang, Longhui</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Quadrifocal Tensor SFM Photogrammetry Positioning and Calibration Technique for HOFS Aerial Sensors</atitle><jtitle>Remote sensing (Basel, Switzerland)</jtitle><date>2022-08-01</date><risdate>2022</risdate><volume>14</volume><issue>15</issue><spage>3521</spage><pages>3521-</pages><issn>2072-4292</issn><eissn>2072-4292</eissn><abstract>Nowadays, the integration between photogrammetry and structure from motion (SFM) has become much closer, and many attempts have been made to combine the two approaches to realize the positioning, calibration, and 3D reconstruction of a large number of images. For the positioning and calibration of high oblique frame sweep (HOFS) aerial cameras, a quadrifocal tensor SFM photogrammetry technique is proposed to resolve the positioning and calibration task of such cameras. It adopts the quadrifocal tensor idea into the OpenMVG SFM pipeline to solve the complexity problem caused by the small single-viewing imaging area and the high image overlapping ratio. It also integrates the photogrammetry iteration idea into the OpenMVG SFM pipeline to enhance the positioning and calibration accuracy, which includes a coarse to fine three-stage Bundle Adjustment (BA) processing approach. In this paper, the overall workflow of the proposed technique was first introduced in detail, from feature extraction and image matching, relative rotation and translation estimation, global rotation and translation estimation, and the quadrifocal tensor model construction to the three-stage BA process and calibration. Then, experiments were carried out in the Zhengzhou area, implementing four types of adjustment methods. The results suggest that the proposed quadrifocal tensor SFM photogrammetry is suitable for large tilt frame sweep camera positioning and calibration without prior information on detailed camera intrinsic parameters and structure. The modifications made to the OpenMVG SFM pipeline enhanced the precision of image positioning and calibration and provided the precision level of professional photogrammetry software.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/rs14153521</doi><orcidid>https://orcid.org/0000-0003-1062-2017</orcidid><orcidid>https://orcid.org/0000-0003-4300-2607</orcidid><orcidid>https://orcid.org/0000-0002-2405-2038</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2072-4292
ispartof Remote sensing (Basel, Switzerland), 2022-08, Vol.14 (15), p.3521
issn 2072-4292
2072-4292
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_ecfa40d993364d099b234435a9add93f
source Publicly Available Content Database
subjects a quadrifocal tensor
Accuracy
Bundle adjustment
Calibration
Cameras
Datasets
Digital cameras
Feature extraction
frame sweep aerial sensor
Image enhancement
Image reconstruction
Iterative methods
Motion perception
oblique photogrammetry
Parameter modification
Photogrammetry
Photography
Remote sensing
Rotation
Semantics
SFM photogrammetry
Software
Tensors
Translation
VisionMap A3 edge sensor
Workflow
title A Quadrifocal Tensor SFM Photogrammetry Positioning and Calibration Technique for HOFS Aerial Sensors
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-24T18%3A32%3A35IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20Quadrifocal%20Tensor%20SFM%20Photogrammetry%20Positioning%20and%20Calibration%20Technique%20for%20HOFS%20Aerial%20Sensors&rft.jtitle=Remote%20sensing%20(Basel,%20Switzerland)&rft.au=Wang,%20Tao&rft.date=2022-08-01&rft.volume=14&rft.issue=15&rft.spage=3521&rft.pages=3521-&rft.issn=2072-4292&rft.eissn=2072-4292&rft_id=info:doi/10.3390/rs14153521&rft_dat=%3Cproquest_doaj_%3E2700764760%3C/proquest_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c320t-103109a9e32cee6022d598b55f3c1f8bae308654d6d70873b36e68ab21c92d723%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2700764760&rft_id=info:pmid/&rfr_iscdi=true