{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:32:28Z","timestamp":1760236348175,"version":"build-2065373602"},"reference-count":37,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2021,11,15]],"date-time":"2021-11-15T00:00:00Z","timestamp":1636934400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41771493 and 41101407"],"award-info":[{"award-number":["41771493 and 41101407"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"self-determined research funds of CCNU from the basic research and operation of MOE","award":["CCNU19TS002"],"award-info":[{"award-number":["CCNU19TS002"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>To reduce the 3D systematic error of the RGB-D camera and improve the measurement accuracy, this paper is the first to propose a new 3D compensation method for the systematic error of a Kinect V2 in a 3D calibration field. The processing of the method is as follows. First, the coordinate system between the RGB-D camera and 3D calibration field is transformed using 3D corresponding points. Second, the inliers are obtained using the Bayes SAmple Consensus (BaySAC) algorithm to eliminate gross errors (i.e., outliers). Third, the parameters of the 3D registration model are calculated by the iteration method with variable weights that can further control the error. Fourth, three systematic error compensation models are established and solved by the stepwise regression method. Finally, the optimal model is selected to calibrate the RGB-D camera. The experimental results show the following: (1) the BaySAC algorithm can effectively eliminate gross errors; (2) the iteration method with variable weights could better control slightly larger accidental errors; and (3) the 3D compensation method can compensate 91.19% and 61.58% of the systematic error of the RGB-D camera in the depth and 3D directions, respectively, in the 3D control field, which is superior to the 2D compensation method. The proposed method can control three types of errors (i.e., gross errors, accidental errors and systematic errors) and model errors and can effectively improve the accuracy of depth data.<\/jats:p>","DOI":"10.3390\/rs13224583","type":"journal-article","created":{"date-parts":[[2021,11,15]],"date-time":"2021-11-15T20:46:47Z","timestamp":1637009207000},"page":"4583","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A 3D Compensation Method for the Systematic Errors of Kinect V2"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2988-798X","authenticated-orcid":false,"given":"Chang","family":"Li","sequence":"first","affiliation":[{"name":"Key Laboratory for Geographical Process Analysis & Simulation, Central China Normal University, Wuhan 430079, China"},{"name":"College of Urban and Environmental Science, Central China Normal University, Wuhan 430079, China"}]},{"given":"Bingrui","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory for Geographical Process Analysis & Simulation, Central China Normal University, Wuhan 430079, China"},{"name":"College of Urban and Environmental Science, Central China Normal University, Wuhan 430079, China"}]},{"given":"Sisi","family":"Zhao","sequence":"additional","affiliation":[{"name":"Vivo Mobile Communication Co., Ltd., Hangzhou 310030, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"93","DOI":"10.5194\/isprsarchives-XL-5-W4-93-2015","article-title":"First Experiences with Kinect V2 Sensor For Close Range 3d Modelling","volume":"XL-5\/W4","author":"Lachat","year":"2015","journal-title":"ISPRS-Int. 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