This paper discusses the issue of automation of orthoimage generation based on Terrestrial Laser Scanning (TLS) data and digital images. The following two problems are discussed: automatic generation of projection planes based on TLS data, and automatic orientation of digital images in relation to TLS data. The majority of popular software applications use manual definitions of projection planes. However, the authors propose an original software tool to address the first issue, which defines important planes based on a TLS point cloud utilizing different algorithms (RANdom SAmple Consensus-RANSAC, Hough transform, "region growing"). To address the second task, the authors present a series of algorithms for automated digital image orientation in relation to a point cloud. This is important in cases where scans and images are acquired from different places and at different times. The algorithms utilize Scale Invariant Feature Transform(SIFT) operators in order to find points that correspond in reflectance intensity between coloure images (Red Green Blue-RGB) and orthoimages, based on TLS data. The paper also presents a verification method using SIFT and Speeded-Up Robust Features (SURF) operators. The research results in an original tool and applied Computer Vision(CV) algorithms that improve the process of orthoimage generation.
This paper discusses the issue of the influence of cartographic Terrestrial Laser Scanning (TLS) data conversion into feature-based automatic registration. Automatic registration of data is a multi-stage process, it is based on original software tools and consists of: (1) Conversion of data to the raster form, (2) register of TLS data in pairs in all possible combinations using the SURF (Speeded Up Robust Features) and FAST (Features from Accelerated Segment Test) algorithms, (3) the quality analysis of relative orientation of processed pairs, and (4) the final bundle adjustment. The following two problems, related to the influence of the spherical image, the orthoimage and the Mercator representation of the point cloud, are discussed: The correctness of the automatic tie points detection and distribution and the influence of the TLS position on the completeness of the registration process and the quality assessment. The majority of popular software applications use manually or semi-automatically determined corresponding points. However, the authors propose an original software tool to address the first issue, which automatically detects and matches corresponding points on each TLS raster representation, utilizing different algorithms (SURF and FAST). To address the second task, the authors present a series of analyses: The time of detection of characteristic points, the percentage of incorrectly detected points and adjusted characteristic points, the number of detected control and check points, the orientation accuracy of control and check points, and the distribution of control and check points. Selection of an appropriate method for the TLS point cloud conversion to the raster form and selection of an appropriate algorithm, considerably influence the completeness of the entire process, and the accuracy of data orientation. The results of the performed experiments show that fully automatic registration of the TLS point clouds in the raster forms is possible; however, it is not possible to propose one, universal form of the point cloud, because a priori knowledge concerning the scanner positions is required. If scanner stations are located close to one another in raster images or in spherical images, Mercator projections are recommended. In the case where fragments of the surface are measured under different angles from different distances and heights of the TLS, orthoimages are suggested.
Commission IIKEY WORDS: cultural heritage, tower verticality, structure from motion (SFM), multi-view stereo (MVS), terrestrial laser scanning (TLS), UAV ABSTRACT:This paper presents an analysis of source photogrammetric data in relation to the examination of verticality in a monumental tower. In the proposed data processing methodology, the geometric quality of the point clouds relating to the monumental tower of the castle in Iłżawas established by using terrestrial laser scanning (Z+F 5006h, Leica C10), terrestrial photographs and digital images sourced via unmanned aerial vehicles (UAV) (Leica Aibot X6 Hexacopter). Tests were performed using the original software, developed by the authors, which allows for the automation of 3D point cloud processing. The software also facilitates the verification of the verticality of the tower and the assessment of the quality of utilized data.
ABSTRACT:Updating the cadastre requires much work carried out by surveying companies in countries that have still not solved the problem of updating the cadastral data. In terms of the required precision, these works are among the most accurate. This raises the question: to what extent may modern digital photogrammetric methods be useful in this process? The capabilities of photogrammetry have increased significantly after the introduction of digital aerial cameras and digital technologies. For the registration of cadastral objects, i.e., land parcels' boundaries and the outlines of buildings, very high-resolution aerial photographs can be used. The paper relates an attempt to use an alternative source of data for this task -the development of images acquired from UAS platforms. Multivariate mapping of cadastral parcels was implemented to determine the scope of the suitability of low altitude photos for the cadastre. In this study, images obtained from UAS with the GSD of 3 cm were collected for an area of a few square kilometres. Bundle adjustment of these data was processed with sub-pixel accuracy. This led to photogrammetric measurements being carried out and the provision of an orthophotomap (orthogonalized with a digital surface model from dense image matching of UAS images). Geometric data related to buildings were collected with two methods: stereoscopic and multi-photo measurements. Data related to parcels' boundaries were measured with monoplotting on an orthophotomap from low-altitude images. As reference field surveying data were used. The paper shows the potential and limits of the use of UAS in a process of updating cadastral data. It also gives recommendations when performing photogrammetric missions and presents the possible accuracy of this type of work.
Commission VI, WG V/2 KEY WORDS: Terrestrial scanning, dense image matching, monumental objects, orthoimages ABSTRACT:Cultural heritage is the evidence of the past; monumental objects create the important part of the cultural heritage. Selection of a method to be applied depends on many factors, which include: the objectives of inventory, the object's volume, sumptuousness of architectural design, accessibility to the object, required terms and accuracy of works. The paper presents research and experimental works, which have been performed in the course of development of architectural documentation of elements of the external facades and interiors of the Wilanów Palace Museum in Warszawa. Point clouds, acquired from terrestrial laser scanning (Z+F 5003h) and digital images taken with Nikon D3X and Hasselblad H4D cameras were used. Advantages and disadvantages of utilisation of these technologies of measurements have been analysed with consideration of the influence of the structure and reflectance of investigated monumental surfaces on the quality of generation of photogrammetric products. The geometric quality of surfaces obtained from terrestrial laser scanning data and from point clouds resulting from digital images, have been compared.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.