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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...
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Published in: | Remote sensing (Basel, Switzerland) Switzerland), 2022-08, Vol.14 (15), p.3521 |
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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. |
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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 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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 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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> |
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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 |
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