{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:53:36Z","timestamp":1760147616509,"version":"build-2065373602"},"reference-count":95,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,2,18]],"date-time":"2023-02-18T00:00:00Z","timestamp":1676678400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100014434","name":"Polish National Agency for Academic Exchange","doi-asserted-by":"publisher","award":["BPN\/BEK\/2021\/1\/00246\/U\/00001"],"award-info":[{"award-number":["BPN\/BEK\/2021\/1\/00246\/U\/00001"]}],"id":[{"id":"10.13039\/501100014434","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This paper presents the CRBeDaSet\u2014a new benchmark dataset designed for evaluating close range, image-based 3D modeling and reconstruction techniques, and the first empirical experiences of its use. The test object is a medium-sized building. Diverse textures characterize the surface of elevations. The dataset contains: the geodetic spatial control network (12 stabilized ground points determined using iterative multi-observation parametric adjustment) and the photogrammetric network (32 artificial signalized and 18 defined natural control points), measured using Leica TS30 total station and 36 terrestrial, mainly convergent photos, acquired from elevated camera standpoints with non-metric digital single-lens reflex Nikon D5100 camera (ground sample distance approx. 3 mm), the complex results of the bundle block adjustment with simultaneous camera calibration performed in the Pictran software package, and the colored point clouds (ca. 250 million points) from terrestrial laser scanning acquired using the Leica ScanStation C10 and post-processed in the Leica Cyclone\u2122 SCAN software (ver. 2022.1.1) which were denoized, filtered, and classified using LoD3 standard (ca. 62 million points). The existing datasets and benchmarks were also described and evaluated in the paper. The proposed photogrammetric dataset was experimentally tested in the open-source application GRAPHOS and the commercial suites ContextCapture, Metashape, PhotoScan, Pix4Dmapper, and RealityCapture. As the first experience in its evaluation, the difficulties and errors that occurred in the software used during dataset digital processing were shown and discussed. The proposed CRBeDaSet benchmark dataset allows obtaining high accuracy (\u201cmm\u201d range) of the photogrammetric 3D object reconstruction in close range, based on a multi-image view uncalibrated imagery, dense image matching techniques, and generated dense point clouds.<\/jats:p>","DOI":"10.3390\/rs15041116","type":"journal-article","created":{"date-parts":[[2023,2,20]],"date-time":"2023-02-20T01:36:37Z","timestamp":1676856997000},"page":"1116","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["CRBeDaSet: A Benchmark Dataset for High Accuracy Close Range 3D Object Reconstruction"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6714-2519","authenticated-orcid":false,"given":"Grzegorz","family":"Gabara","sequence":"first","affiliation":[{"name":"Department of Photogrammetry, Remote Sensing and Spatial Information Systems, Faculty of Geodesy and Cartography, Warsaw University of Technology, Pl. Politechniki 1, 00-661 Warsaw, Poland"},{"name":"Institute for Photogrammetry, University of Stuttgart, Geschwister-Scholl-Strasse 24, 70174 Stuttgart, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8895-0291","authenticated-orcid":false,"given":"Piotr","family":"Sawicki","sequence":"additional","affiliation":[{"name":"Independent Researcher, 10-696 Olsztyn, Poland"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,18]]},"reference":[{"key":"ref_1","first-page":"305","article-title":"Automated 3D Object Reconstruction via Multi-Image Close-Range Photogrammetry","volume":"38","author":"Jazayeri","year":"2010","journal-title":"ISPRS Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"355","DOI":"10.5194\/isprs-archives-XLII-2-355-2018","article-title":"Position Accuracy Analysis of a Robust Vision-Based Navigation","volume":"42","author":"Gaglione","year":"2018","journal-title":"ISPRS Int. Arch. Photogramm. 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