Relevant bibliographies by topics / 3D point cloud modeling

Academic literature on the topic '3D point cloud modeling'

Author: Grafiati
Published: 14 March 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Contents

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic '3D point cloud modeling.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "3D point cloud modeling"

1

Özdemir, E., and F. Remondino. "SEGMENTATION OF 3D PHOTOGRAMMETRIC POINT CLOUD FOR 3D BUILDING MODELING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W10 (September 12, 2018): 135–42. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w10-135-2018.

Full text
Abstract:
<p><strong>Abstract.</strong> 3D city modeling has become important over the last decades as these models are being used in different studies including, energy evaluation, visibility analysis, 3D cadastre, urban planning, change detection, disaster management, etc. Segmentation and classification of photogrammetric or LiDAR data is important for 3D city models as these are the main data sources, and, these tasks are challenging due to their complexity. This study presents research in progress, which focuses on the segmentation and classification of 3D point clouds and orthoimages to generate 3D urban models. The aim is to classify photogrammetric-based point clouds (&amp;gt;<span class="thinspace"></span>30<span class="thinspace"></span>pts/sqm) in combination with aerial RGB orthoimages (~<span class="thinspace"></span>10<span class="thinspace"></span>cm, RGB image) in order to name buildings, ground level objects (GLOs), trees, grass areas, and other regions. If on the one hand the classification of aerial orthoimages is foreseen to be a fast approach to get classes and then transfer them from the image to the point cloud space, on the other hand, segmenting a point cloud is expected to be much more time consuming but to provide significant segments from the analyzed scene. For this reason, the proposed method combines segmentation methods on the two geoinformation in order to achieve better results.</p>
APA, Harvard, Vancouver, ISO, and other styles
2

Yang, Zeyin. "3D Modeling of Sculpture Nano-Ceramics under Sparse Image Sequence." International Journal of Analytical Chemistry 2022 (July 7, 2022): 1–8. http://dx.doi.org/10.1155/2022/5710535.

Full text
Abstract:
To improve the analysis ability of point cloud 3D reconstruction of sparse images of nano-ceramic sculpture points, an automatic cloud 3D reconstruction method of nano-ceramic sculpture points based on sparse image sequence is proposed. Firstly, 3D angle detection and edge contour feature extraction methods are used to analyze 3D point cloud features of nano-ceramic sculpture point save image; secondly, the point cloud of the fuel economy image of nano-ceramic sculpture points is merged and the sloping action method is used to shape degradation to realize the information increase and fusion filtering of the fuel economy image of nano-ceramic sculpture points; finally, combined with the local mean denoising method, image is refined to improve the ability of sparse image outline structure of nano-ceramic sculpture points. The simulation results show that this method has high accuracy, good image matching ability, and high signal-to-noise ratio.
APA, Harvard, Vancouver, ISO, and other styles
3

Gong, Jingyu, Zhou Ye, and Lizhuang Ma. "Neighborhood co-occurrence modeling in 3D point cloud segmentation." Computational Visual Media 8, no. 2 (December 6, 2021): 303–15. http://dx.doi.org/10.1007/s41095-021-0244-6.

Full text
Abstract:
AbstractA significant performance boost has been achieved in point cloud semantic segmentation by utilization of the encoder-decoder architecture and novel convolution operations for point clouds. However, co-occurrence relationships within a local region which can directly influence segmentation results are usually ignored by current works. In this paper, we propose a neighborhood co-occurrence matrix (NCM) to model local co-occurrence relationships in a point cloud. We generate target NCM and prediction NCM from semantic labels and a prediction map respectively. Then, Kullback-Leibler (KL) divergence is used to maximize the similarity between the target and prediction NCMs to learn the co-occurrence relationship. Moreover, for large scenes where the NCMs for a sampled point cloud and the whole scene differ greatly, we introduce a reverse form of KL divergence which can better handle the difference to supervise the prediction NCMs. We integrate our method into an existing backbone and conduct comprehensive experiments on three datasets: Semantic3D for outdoor space segmentation, and S3DIS and ScanNet v2 for indoor scene segmentation. Results indicate that our method can significantly improve upon the backbone and outperform many leading competitors.
APA, Harvard, Vancouver, ISO, and other styles
4

Wu, Youping, and Zhihui Zhou. "Intelligent City 3D Modeling Model Based on Multisource Data Point Cloud Algorithm." Journal of Function Spaces 2022 (July 21, 2022): 1–10. http://dx.doi.org/10.1155/2022/6135829.

Full text
Abstract:
With the rapid development of smart cities, intelligent navigation, and autonomous driving, how to quickly obtain 3D spatial information of urban buildings and build a high-precision 3D fine model has become a key problem to be solved. As the two-dimensional mapping results have constrained various needs in people’s social life, coupled with the concept of digital city and advocacy, making three-dimensional, virtualization and actualization become the common pursuit of people’s goals. However, the original point cloud obtained is always incomplete due to reasons such as occlusion during acquisition and data density decreasing with distance, resulting in extracted boundaries that are often incomplete as well. In this paper, based on the study of current mainstream 3D model data organization methods, geographic grids and map service specifications, and other related technologies, an intelligent urban 3D modeling model based on multisource data point cloud algorithm is designed for the two problems of unified organization and expression of urban multisource 3D model data. A point cloud preprocessing process is also designed: point cloud noise reduction and downsampling to ensure the original point cloud geometry structure remain unchanged, while improving the point cloud quality and reducing the number of point clouds. By outputting to a common 3D format, the 3D model constructed in this paper can be applied to many fields such as urban planning and design, architectural landscape design, urban management, emergency disaster relief, environmental protection, and virtual tourism.
APA, Harvard, Vancouver, ISO, and other styles
5

Nakagawa, M., T. Yamamoto, S. Tanaka, M. Shiozaki, and T. Ohhashi. "TOPOLOGICAL 3D MODELING USING INDOOR MOBILE LIDAR DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-4/W5 (May 11, 2015): 13–18. http://dx.doi.org/10.5194/isprsarchives-xl-4-w5-13-2015.

Full text
Abstract:
We focus on a region-based point clustering to extract a polygon from a massive point cloud. In the region-based clustering, RANSAC is a suitable approach for estimating surfaces. However, local workspace selection is required to improve a performance in a surface estimation from a massive point cloud. Moreover, the conventional RANSAC is hard to determine whether a point lies inside or outside a surface. In this paper, we propose a method for panoramic rendering-based polygon extraction from indoor mobile LiDAR data. Our aim was to improve region-based point cloud clustering in modeling after point cloud registration. First, we propose a point cloud clustering methodology for polygon extraction on a panoramic range image generated with point-based rendering from a massive point cloud. Next, we describe an experiment that was conducted to verify our methodology with an indoor mobile mapping system in an indoor environment. This experiment was wall-surface extraction using a rendered point cloud from some viewpoints over a wide indoor area. Finally, we confirmed that our proposed methodology could achieve polygon extraction through point cloud clustering from a complex indoor environment.
APA, Harvard, Vancouver, ISO, and other styles
6

Sanchez, J., F. Denis, F. Dupont, L. Trassoudaine, and P. Checchin. "DATA-DRIVEN MODELING OF BUILDING INTERIORS FROM LIDAR POINT CLOUDS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-2-2020 (August 3, 2020): 395–402. http://dx.doi.org/10.5194/isprs-annals-v-2-2020-395-2020.

Full text
Abstract:
Abstract. This paper deals with 3D modeling of building interiors from point clouds captured by a 3D LiDAR scanner. Indeed, currently, the building reconstruction processes remain mostly manual. While LiDAR data have some specific properties which make the reconstruction challenging (anisotropy, noise, clutters, etc.), the automatic methods of the state-of-the-art rely on numerous construction hypotheses which yield 3D models relatively far from initial data. The choice has been done to propose a new modeling method closer to point cloud data, reconstructing only scanned areas of each scene and excluding occluded regions. According to this objective, our approach reconstructs LiDAR scans individually using connected polygons. This modeling relies on a joint processing of an image created from the 2D LiDAR angular sampling and the 3D point cloud associated to one scan. Results are evaluated on synthetic and real data to demonstrate the efficiency as well as the technical strength of the proposed method.
APA, Harvard, Vancouver, ISO, and other styles
7

Liu, Shan, Guanghong Gong, Luhao Xiao, Mengyuan Sun, and Zhengliang Zhu. "Study of rapid face modeling technology based on Kinect." International Journal of Modeling, Simulation, and Scientific Computing 09, no. 01 (January 23, 2018): 1750054. http://dx.doi.org/10.1142/s1793962317500544.

Full text
Abstract:
This paper improves the algorithm of point cloud filtering and registration in 3D modeling, aiming for smaller sampling error and shorter processing time of point cloud data. Based on collaborative sampling among several Kinect devices, we analyze the deficiency of current filtering algorithm, and use a novel method of point cloud filtering. Meanwhile, we use Fast Point Feature Histogram (FPFH) algorithm for feature extraction and point cloud registration. Compared with the aligning process using Point Feature Histograms (PFH), it only takes 9[Formula: see text]min when the number of points is about 500,000, shortening the aligning time by 47.1%. To measure the accuracy of the registration, we propose an algorithm which calculates the average distance of the corresponding coincident parts of two point clouds, and we improve the accuracy to an average distance of 0.7[Formula: see text]mm. In the surface reconstruction section, we adopt Ball Pivoting algorithm for surface reconstruction, obtaining image with higher accuracy in a shorter time.
APA, Harvard, Vancouver, ISO, and other styles
8

Zainuddin, K., Z. Majid, M. F. M. Ariff, K. M. Idris, M. A. Abbas, and N. Darwin. "3D MODELING FOR ROCK ART DOCUMENTATION USING LIGHTWEIGHT MULTISPECTRAL CAMERA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W9 (January 31, 2019): 787–93. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w9-787-2019.

Full text
Abstract:
<p><strong>Abstract.</strong> This paper discusses the use of the lightweight multispectral camera to acquire three-dimensional data for rock art documentation application. The camera consists of five discrete bands, used for taking the motifs of the rock art paintings on a big structure of a cave based on the close-range photogrammetry technique. The captured images then processed using commercial structure-from-motion photogrammetry software, which automatically extracts the tie point. The extracted tie points were then used as input to generate a dense point cloud based on the multi-view stereo (MVS) and produced the multispectral 3D model, and orthophotos in a different wavelength. For comparison, the paintings and the wall surface also observed by using terrestrial laser scanner which capable of recording thousands of points in a short period of time with high accuracy. The cloud-to-cloud comparison between multispectral and TLS 3D point cloud show a sub-cm discrepancy, considering the used of the natural features as control target during 3D construction. Nevertheless, the processing also provides photorealistic orthophoto, indicates the advantages of the multispectral camera in generating dense 3D point cloud as TLS, photorealistic 3D model as RGB optic camera, and also with the multiwavelength output.</p>
APA, Harvard, Vancouver, ISO, and other styles
9

Chibunichev, A. G., and V. P. Galakhov. "IMAGE TO POINT CLOUD METHOD OF 3D-MODELING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXIX-B3 (July 23, 2012): 13–16. http://dx.doi.org/10.5194/isprsarchives-xxxix-b3-13-2012.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Hsieh, Chia-Sheng, and Xiang-Jie Ruan. "Automated Semantic Segmentation of Indoor Point Clouds from Close-Range Images with Three-Dimensional Deep Learning." Buildings 13, no. 2 (February 9, 2023): 468. http://dx.doi.org/10.3390/buildings13020468.

Full text
Abstract:
The creation of building information models requires acquiring real building conditions. The generation of a three-dimensional (3D) model from 3D point clouds involves classification, outline extraction, and boundary regularization for semantic segmentation. The number of 3D point clouds generated using close-range images is smaller and tends to be unevenly distributed, which is not conducive to automated modeling processing. In this paper, we propose an efficient solution for the semantic segmentation of indoor point clouds from close-range images. A 3D deep learning framework that achieves better results is further proposed. A dynamic graph convolutional neural network (DGCNN) 3D deep learning method is used in this study. This method was selected to learn point cloud semantic features. Moreover, more efficient operations can be designed to build a module for extracting point cloud features such that the problem of inadequate beam and column classification can be resolved. First, DGCNN is applied to learn and classify the indoor point cloud into five categories: columns, beams, walls, floors, and ceilings. Then, the proposed semantic segmentation and modeling method is utilized to obtain the geometric parameters of each object to be integrated into building information modeling software. The experimental results show that the overall accuracy rates of the three experimental sections of Area_1 in the Stanford 3D semantic dataset test results are 86.9%, 97.4%, and 92.5%. The segmentation accuracy of corridor 2F in a civil engineering building is 94.2%. In comparing the length with the actual on-site measurement, the root mean square error is found to be ±0.03 m. The proposed method is demonstrated to be capable of automatic semantic segmentation from 3D point clouds with indoor close-range images.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "3D point cloud modeling"

1

Dahlin, Johan. "3D Modeling of Indoor Environments." Thesis, Linköpings universitet, Reglerteknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-93999.

Full text
Abstract:
With the aid of modern sensors it is possible to create models of buildings. These sensorstypically generate 3D point clouds and in order to increase interpretability and usability,these point clouds are often translated into 3D models.In this thesis a way of translating a 3D point cloud into a 3D model is presented. The basicfunctionality is implemented using Matlab. The geometric model consists of floors, wallsand ceilings. In addition, doors and windows are automatically identified and integrated intothe model. The resulting model also has an explicit representation of the topology betweenentities of the model. The topology is represented as a graph, and to do this GraphML isused. The graph is opened in a graph editing program called yEd.The result is a 3D model that can be plotted in Matlab and a graph describing the connectivitybetween entities. The GraphML file is automatically generated in Matlab. An interfacebetween Matlab and yEd allows the user to choose which rooms should be plotted.
APA, Harvard, Vancouver, ISO, and other styles
2

Hammoudi, Karim. "Contributions to the 3D city modeling : 3D polyhedral building model reconstruction from aerial images and 3D facade modeling from terrestrial 3D point cloud and images." Phd thesis, Université Paris-Est, 2011. http://tel.archives-ouvertes.fr/tel-00682442.

Full text
Abstract:
The aim of this work is to develop research on 3D building modeling. In particular, the research in aerial-based 3D building reconstruction is a topic very developed since 1990. However, it is necessary to pursue the research since the actual approaches for 3D massive building reconstruction (although efficient) still encounter problems in generalization, coherency, accuracy. Besides, the recent developments of street acquisition systems such as Mobile Mapping Systems open new perspectives for improvements in building modeling in the sense that the terrestrial data (very dense and accurate) can be exploited with more performance (in comparison to the aerial investigation) to enrich the building models at facade level (e.g., geometry, texturing).Hence, aerial and terrestrial based building modeling approaches are individually proposed. At aerial level, we describe a direct and featureless approach for simple polyhedral building reconstruction from a set of calibrated aerial images. At terrestrial level, several approaches that essentially describe a 3D urban facade modeling pipeline are proposed, namely, the street point cloud segmentation and classification, the geometric modeling of urban facade and the occlusion-free facade texturing
APA, Harvard, Vancouver, ISO, and other styles
3

Bose, Saptak. "An integrated approach encompassing point cloud manipulation and 3D modeling for HBIM establishment: a case of study." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.

Find full text
Abstract:
In the case of Cultural Heritage buildings, the need for an effective, exhaustive, efficient method to replicate its state of being in an interactive, three-dimensional environment is today, of paramount importance, both from an engineering as well as a historical point of view. Modern geomatics entails the usage of Terrestrial Laser Scanners (TLS) and photogrammetric modelling from Structure-from-Motion (SfM) techniques to initiate this modelling operation. To realize its eventual existence, the novel Historic Building Information Modelling (HBIM) technique is implemented. A prototype library of parametric objects, based on historic architectural data, HBIM allows the generation of an all-encompassing, three-dimensional model which possesses an extensive array of information pertaining to the structure at hand. This information, be it geometric, architectural, or even structural, can then be used to realize reinforcement requirements, rehabilitation needs, stage of depreciation, method of initial construction, material makeup, historic alterations, etc. In this paper, the study of the San Michele in Acerboli’s church, located in Santarcangelo di Romagna, Italy, is considered. A HBIM model is prepared and its accuracy analyzed. The final model serves as an information repository for the aforementioned Church, able to geometrically define its finest characteristics.
APA, Harvard, Vancouver, ISO, and other styles
4

Truong, Quoc Hung. "Knowledge-based 3D point clouds processing." Phd thesis, Université de Bourgogne, 2013. http://tel.archives-ouvertes.fr/tel-00977434.

Full text
Abstract:
The modeling of real-world scenes through capturing 3D digital data has proven to be both useful andapplicable in a variety of industrial and surveying applications. Entire scenes are generally capturedby laser scanners and represented by large unorganized point clouds possibly along with additionalphotogrammetric data. A typical challenge in processing such point clouds and data lies in detectingand classifying objects that are present in the scene. In addition to the presence of noise, occlusionsand missing data, such tasks are often hindered by the irregularity of the capturing conditions bothwithin the same dataset and from one data set to another. Given the complexity of the underlyingproblems, recent processing approaches attempt to exploit semantic knowledge for identifying andclassifying objects. In the present thesis, we propose a novel approach that makes use of intelligentknowledge management strategies for processing of 3D point clouds as well as identifying andclassifying objects in digitized scenes. Our approach extends the use of semantic knowledge to allstages of the processing, including the guidance of the individual data-driven processing algorithms.The complete solution consists in a multi-stage iterative concept based on three factors: the modeledknowledge, the package of algorithms, and a classification engine. The goal of the present work isto select and guide algorithms following an adaptive and intelligent strategy for detecting objects inpoint clouds. Experiments with two case studies demonstrate the applicability of our approach. Thestudies were carried out on scans of the waiting area of an airport and along the tracks of a railway.In both cases the goal was to detect and identify objects within a defined area. Results show that ourapproach succeeded in identifying the objects of interest while using various data types
APA, Harvard, Vancouver, ISO, and other styles
5

Yang, Xiucheng. "3D modeling of built heritage : from geometric models to HBIM." Thesis, Strasbourg, 2018. http://www.theses.fr/2018STRAD054/document.

Full text
Abstract:
La maquette numérique de bâtiments historiques (Heritage-BIM) est devenue un enjeu majeur dans la modélisation. Le modèle HBIM ainsi obtenu comprend une description paramétrique et sémantique des éléments constitutifs du patrimoine. La thèse présente des méthodes de constructions HBIM à partir de la documentation historique, de nuages de points, de maillage de surfaces et de géométrie solide. Un concept de mesh-to-HBIM est proposé à l'aide de la programmation visuelle, qui permet de transformer les « familles » paramétriques et les structures géométriques en modèles paramétriques et sémantiques HBIM. La modélisation paramétrique HBIM consiste à créer manuellement des Familles Revit paramétriques et une reconstruction de bâtiment semi-automatisée par l'application de scripts Dynamo. Le processus de modélisation sémantique HBIM transforme directement des géométries segmentées de maillages ou de solides vers l'environnement BIM. Les éléments segmentés et individualisés peuvent être stockés et gérés dans cet environnement avec des compléments d'informations d'association entre éléments
Heritage Building Information Modelling (HBIM) is a major issue in heritage documentation and conservation. The obtained HBIM model provides a parametric and semantic description of the heritage elements. This thesis presents methods for the generation of HBIM models from point clouds (obtained by photogrammetry or laser scanning), surface mesh and solid geometry. A concept of solid/mesh-to-HBIM is proposed using Autodesk Dynamo visual programming, which transfers the parametric “Family” and geometric structures to parametric and semantic HBIM models. The parametric HBIM modelling process involves conventional manual parametric “Family” creation and semi-automated building reconstruction by Dynamo. The semantic HBIM modelling process directly transfers the segmented solid geometry and closed mesh-to-BIM environment. The segmented elements can be stored and managed in the BIM environment with attached attributes information and relationships established among the elements
APA, Harvard, Vancouver, ISO, and other styles
6

De, Pellegrini Martin. "Mobile-based 3D modeling : An indepth evaluation for the application to maintenance and supervision." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-298024.

Full text
Abstract:
Indoor environment modeling has become a relevant topic in several applications fields including Augmented, Virtual and Mixed Reality. Furthermore, with the Digital Transformation, many industries have moved toward this technology trying to generate detailed models of an environment allowing the viewers to navigate through it or mapping surfaces to insert virtual elements in a real scene. Therefore, this Thesis project has been conducted with the purpose to review well- established deterministic methods for 3D scene reconstruction and researching the state- of- the- art, such as machine learning- based approaches, and a possible implementation on mobile devices. Initially, we focused on the well- established methods such as Structure from Motion (SfM) that use photogrammetry to estimate camera poses and depth using only RGB images. Lastly, the research has been centered on the most innovative methods that make use of machine learning to predict depth maps and camera poses from a video stream. Most of the methods reviewed are completely unsupervised and are based on a combination of two subnetwork, the disparity network (DispNet) for the depth estimation and pose network (PoseNet) for camera pose estimation. Despite the fact that the results in outdoor application show high quality depth map and and reliable odometry, there are still some limitations for the deployment of this technology in indoor environment. Overall, the results are promising.
Modellering av inomhusmiljö har blivit ett relevant ämne inom flera applikationsområden, inklusive Augmented, Virtual och Mixed Reality. Dessutom, med den digitala transformationen, har många branscher gått mot denna teknik som försöker generera detaljerade modeller av en miljö som gör det möjligt för tittarna att navigera genom den eller kartlägga ytor för att infoga virtuella element i en riktig scen. Därför har detta avhandlingsprojekt genomförts med syftet att granska väletablerade deterministiska metoder för 3Dscenrekonstruktion och undersöka det senaste inom teknik, såsom maskininlärningsbaserade metoder och en möjlig implementering på mobil. Inledningsvis fokuserade vi på de väletablerade metoderna som Structure From Motion (SfM) som använder fotogrammetri för att uppskatta kameraställningar och djup med endast RGBbilder. Slutligen har forskningen varit inriktad på de mest innovativa metoderna som använder maskininlärning för att förutsäga djupkartor och kameraposer från en videoström. De flesta av de granskade metoderna är helt utan tillsyn och baseras på en kombination av två undernätverk, skillnadsnätverket (DispNet) för djupuppskattning och posenätverk (PoseNet) för kameraposestimering. Trots att resultaten i utomhusanvändning visar djupkarta av hög kvalitet och tillförlitlig vägmätning, finns det fortfarande vissa begränsningar för användningen av denna teknik i inomhusmiljön, men ändå är resultaten lovande.
APA, Harvard, Vancouver, ISO, and other styles
7

Carlsson, Henrik. "Modeling method to visually reconstruct the historical Vasa ship with the help of a 3D scanned point cloud." Thesis, Högskolan i Gävle, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-10574.

Full text
Abstract:
A point cloud derived from scanning the actual Vasa ship is used for an accurate visualisation. Both manual and automatic mesh techniques where utilized in the modelling of the Vasa ship to overcome problems of poor resolution in the point cloud and computing power. A combination of manual and automatic techniques resulted in a 3D model optimized for use within animation software. The method presented in this paper utilized a method that allows the user to keep control over topology.  The polygon count is kept to a minimum and one can still remain certain that the measurements and realism from the point cloud is maintained.
APA, Harvard, Vancouver, ISO, and other styles
8

Fjärdsjö, Johnny, and Zada Nasir Muhabatt. "Kvalitetssäkrad arbetsprocess vid 3D-modellering av byggnader : Baserat på underlag från ritning och 3D-laserskanning." Thesis, KTH, Byggteknik och design, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-148822.

Full text
Abstract:
Tidigare vid ombyggnation, försäljning och förvaltning av byggnader som var uppförda innan 80-talet utgick fastighetsägarna från enkla handritade pappersritningar. Det är en svår utmaning att hålla ritningen uppdaterad till verkliga förhållanden d.v.s. relationsritning. För ca 25 år sedan (i början på 80-talet) byttes papper och penna ut mot avancerade ritprogram (CAD) för framtagning av ritningar. Idag används CAD i stort sett för all nyprojektering och de senaste åren har utvecklingen gått mot en större användning av 3D-underlag än tidigare 2D-ritningar. Den stora fördelen med att projektera i 3D är att en virtuell modell skapas av hela byggnaden för att få en bättre kontroll av ingående byggdelsobjekt och även att fel kan upptäckas i tidigare skeden än på byggarbetsplatsen. Genom att börja bygga en virtuell byggnad i 3D från första skedet och succesivt fylla den med mer relevant information i hela livscykeln får man en komplett informationsmodell. Ett av kraven som ställs på fastighetsägarna vid ombyggnation och förvaltning är att tillhandahålla korrekt information och uppdaterade ritningar. Det skall vara enkelt för entreprenören att avläsa ritningarna. I rapporten beskrivs en effektiviserad arbetsprocess, metoder, verktyg och användningsområden för framtagning av 3D-modeller. Detta arbete avser att leda fram till en metodbeskrivning som skall användas för erfarenhetsåterföring. Arbetet skall också vara ett underlag som skall användas för att beskriva tillvägagångsättet att modellera från äldre ritningar till 3D-modeller. Metodbeskrivningen kommer att förenkla förståelsen för modellering för både fastighetsägaren och inom företaget, samt höja kvalitén på arbetet med att skapa CAD-modeller från de olika underlag som används för modellering.
The use of hand drawn construction model was the only way of development, rebuilding, sales and real estate management before the 80’s. However, the challenge was to preserve the drawings and maintain its real condition. To make things work faster and easier the development of advanced drawing software (CAD) was introduced which replaced the traditional hand drawn designs. Today, CAD is used broadly for all new constructions with a great success rate. However, with the new advanced technology many engineers and construction companies are heavily using 3D models over 2D drawings. The major advantage of designing in 3D is a virtual model created of the entire building to get a better control of input construction items and the errors can be detected at earlier stages than at the construction sites. By modifying buildings in a virtual model in three dimensions yet at the first stage and gradually fill it with more relevant information throughout the life cycle of buildings to get a complete information model. One of the requirements from the property owners in the redevelopment and management is to provide accurate information and updated drawings. It should be simple for the contractor to read drawings. This report describes a streamlined work processes, methods, tools and applications for the production of 3D models. This work is intended to lead to a methodology and to be used as well as for passing on experience. This report will also be a base to describe the approach to model from older drawings into 3D models. The method description will simplify the understanding of model for both the property owners and for companies who creates 3D models. It will also increase the quality of the work to create CAD models from the different data used for modeling.
APA, Harvard, Vancouver, ISO, and other styles
9

Abayowa, Bernard Olushola. "Automatic Registration of Optical Aerial Imagery to a LiDAR Point Cloud for Generation of Large Scale City Models." University of Dayton / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1372508452.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Penk, David. "Vyhotovení 3D modelu části budovy SPŠ stavební Brno." Master's thesis, Vysoké učení technické v Brně. Fakulta stavební, 2021. http://www.nusl.cz/ntk/nusl-444256.

Full text
Abstract:
The thesis deals with the creation of a 3D model from data collected by laser scanning. The first part deals with the theoretical foundations of buildings information modeling and method of laser scanning. The rest of the work describes the detailed process from data collection to the creation of the model. Most of the space is devoted to work in the Revit software environment.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "3D point cloud modeling"

1

Liu, Shan, Min Zhang, Pranav Kadam, and C. C. Jay Kuo. 3D Point Cloud Analysis. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-89180-0.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Zhang, Guoxiang, and YangQuan Chen. Towards Optimal Point Cloud Processing for 3D Reconstruction. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-96110-7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Chen, YangQuan, and Guoxiang Zhang. Towards Optimal Point Cloud Processing for 3D Reconstruction. Springer International Publishing AG, 2022.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

3D Point Cloud Analysis: Traditional, Deep Learning, and Explainable Machine Learning Methods. Springer International Publishing AG, 2021.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

3D Point Cloud Analysis: Traditional, Deep Learning, and Explainable Machine Learning Methods. Springer International Publishing AG, 2022.

Find full text
APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "3D point cloud modeling"

1

Héno, Raphaële, and Laure Chandelier. "Point Cloud Processing." In 3D Modeling of Buildings, 133–81. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118648889.ch5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Cao, Xu, and Katashi Nagao. "Point Cloud Colorization Based on Densely Annotated 3D Shape Dataset." In MultiMedia Modeling, 436–46. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-05710-7_36.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Cheng, Shyi-Chyi, Ting-Lan Lin, and Ping-Yuan Tseng. "K-SVD Based Point Cloud Coding for RGB-D Video Compression Using 3D Super-Point Clustering." In MultiMedia Modeling, 690–701. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-37731-1_56.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Obrock, Lars, and Eberhard Gülch. "Deep Learning Methods for Extracting Object-Oriented Models of Building Interiors from Images." In iCity. Transformative Research for the Livable, Intelligent, and Sustainable City, 267–79. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92096-8_17.

Full text
Abstract:
AbstractIn this chapter, we present an approach of enriching photogrammetric point clouds with semantic information extracted from images of digital cameras or smartphones to enable a later automation of BIM modelling with object-oriented models. Based on the DeepLabv3+ architecture, we extract building components and objects of interiors in full 3D. During the photogrammetric reconstruction, we project the segmented categories derived from the images into the point cloud. Based on the semantic information, we align the point cloud, correct the scale and extract further information. The combined extraction of geometric and semantic information yields a high potential for automated BIM model reconstruction.
APA, Harvard, Vancouver, ISO, and other styles
5

Zhang, Wanyi, Xiuhua Fu, and Wei Li. "3D Modeling System of Lidar Point Cloud Processing Algorithm Based on Artificial Intelligence." In Advances in Intelligent Systems and Computing, 764–70. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-53980-1_112.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Wei, Zheng, Tianyu Yao, and Chenghui Shi. "Research on the Construction of 3D Laser Scanning Tunnel Point Cloud Based on B-spline Interpolation." In Advanced Tunneling Techniques and Information Modeling of Underground Infrastructure, 111–18. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79672-3_8.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Maruyama, Tsubasa, Satoshi Kanai, and Hiroaki Date. "Simulating a Walk of Digital Human Model Directly in Massive 3D Laser-Scanned Point Cloud of Indoor Environments." In Digital Human Modeling and Applications in Health, Safety, Ergonomics, and Risk Management. Human Body Modeling and Ergonomics, 366–75. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39182-8_43.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Pisoni, Isabella Nicole, Alberto Cina, Nives Grasso, and Paolo Maschio. "Techniques and Survey for 3D Modeling of Touristic Caves: Valdemino Case." In Geomatics for Green and Digital Transition, 317–28. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-17439-1_23.

Full text
Abstract:
AbstractNowadays, touristic caves are a relevant topic among topographical and geological studies. Modern techniques allow to elaborate 3D models with high accuracy and precision. Anyway, underground surveys are always delicate to perform, due to narrow and difficult to reach environments. In this paper, we show a case study, “Valdemino” cave, that involved the utilization of different point cloud acquisition methods: UAV, TLS, SLAM. The first purpose was to obtain 3D models of outdoor and indoor environments with a medium and high accuracy. These models were used to calculate the thickness of the rock between surface and cave’s roof and will be used for further studies, taking part in the PRIN 2017 project, concerning the impact of the tourist on show caves. The second purpose was to discuss about the feasibility and precision of the different survey methods, when studying a cave. The results showed how SLAM technology is enough accurate for speleological purposes, if compared with the more accurate TLS method. It is precise, maneuverable, easy to use and it allowed to get into environments that TLS can’t reach, such as non-touristic areas.
APA, Harvard, Vancouver, ISO, and other styles
9

Oreni, Daniela, Raffaella Brumana, Fabrizio Banfi, Luca Bertola, Luigi Barazzetti, Branka Cuca, Mattia Previtali, and Fabio Roncoroni. "Beyond Crude 3D Models: From Point Clouds to Historical Building Information Modeling via NURBS." In Digital Heritage. Progress in Cultural Heritage: Documentation, Preservation, and Protection, 166–75. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13695-0_16.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Zhang, Jing, Maosu Li, Wenjin Zhang, Yijie Wu, and Fan Xue. "Prospect of Architectonic Grammar Reconstruction from Dense 3D Point Clouds: Historical Building Information Modeling (HBIM) of Guangdong Cultural Heritages." In Proceedings of the 25th International Symposium on Advancement of Construction Management and Real Estate, 1421–31. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3587-8_97.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "3D point cloud modeling"

1

Yu, Xumin, Lulu Tang, Yongming Rao, Tiejun Huang, Jie Zhou, and Jiwen Lu. "Point-BERT: Pre-training 3D Point Cloud Transformers with Masked Point Modeling." In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2022. http://dx.doi.org/10.1109/cvpr52688.2022.01871.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Pang, Guan, Rongqi Qiu, Jing Huang, Suya You, and Ulrich Neumann. "Automatic 3D Industrial Point Cloud Classification and Modeling." In SPE Western Regional Meeting. Society of Petroleum Engineers, 2015. http://dx.doi.org/10.2118/174069-ms.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Kawata, Yoshiyuki, Satoshi Yoshii, Yukihiro Funatsu, and Kazuya Takemata. "3D campus modeling using LiDAR point cloud data." In SPIE Remote Sensing, edited by Ulrich Michel, Daniel L. Civco, Manfred Ehlers, Karsten Schulz, Konstantinos G. Nikolakopoulos, Shahid Habib, David Messinger, and Antonino Maltese. SPIE, 2012. http://dx.doi.org/10.1117/12.973652.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Pang, Guan, Rongqi Qiu, Jing Huang, Suya You, and Ulrich Neumann. "Automatic 3D industrial point cloud modeling and recognition." In 2015 14th IAPR International Conference on Machine Vision Applications (MVA). IEEE, 2015. http://dx.doi.org/10.1109/mva.2015.7153124.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Guo, Jianwei, Zhanglin Cheng, Shibiao Xu, and Xiaopeng Zhang. "Realistic procedural plant modeling guided by 3D point cloud." In SIGGRAPH '17: Special Interest Group on Computer Graphics and Interactive Techniques Conference. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3102163.3102193.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Yao, Shuncai, and Jinxuan Shi. "Road 3D Point cloud Data Modeling based on LiDAR." In 2022 4th International Conference on Intelligent Control, Measurement and Signal Processing (ICMSP). IEEE, 2022. http://dx.doi.org/10.1109/icmsp55950.2022.9859099.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Ruiju Zhang, Yanmin Wang, and Daixue Song. "Research and implementation from point cloud to 3D model." In 2010 Second International Conference on Computer Modeling and Simulation (ICCMS 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccms.2010.236.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Tian Qing-guo and Li Jin-tong. "Pre-processing of 3D scanning line point cloud data." In 2010 International Conference on Computer Application and System Modeling (ICCASM 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccasm.2010.5622877.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Guo, Jiateng, Jizhou Jiang, Lixin Wu, Wenhui Zhou, and Lianhuan Wei. "3D modeling for mine roadway from laser scanning point cloud." In IGARSS 2016 - 2016 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2016. http://dx.doi.org/10.1109/igarss.2016.7730160.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Sanchez, Victor, and Avideh Zakhor. "Planar 3D modeling of building interiors from point cloud data." In 2012 19th IEEE International Conference on Image Processing (ICIP 2012). IEEE, 2012. http://dx.doi.org/10.1109/icip.2012.6467225.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "3D point cloud modeling"

1

Smith, Curtis L., Steven Prescott, Kellie Kvarfordt, Ram Sampath, and Katie Larson. Status of the phenomena representation, 3D modeling, and cloud-based software architecture development. Office of Scientific and Technical Information (OSTI), September 2015. http://dx.doi.org/10.2172/1245516.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Blundell, S., and Philip Devine. Creation, transformation, and orientation adjustment of a building façade model for feature segmentation : transforming 3D building point cloud models into 2D georeferenced feature overlays. Engineer Research and Development Center (U.S.), January 2020. http://dx.doi.org/10.21079/11681/35115.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Habib, Ayman, Darcy M. Bullock, Yi-Chun Lin, and Raja Manish. Road Ditch Line Mapping with Mobile LiDAR. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317354.

Full text
Abstract:
Maintenance of roadside ditches is important to avoid localized flooding and premature failure of pavements. Scheduling effective preventative maintenance requires mapping of the ditch profile to identify areas requiring excavation of long-term sediment accumulation. High-resolution, high-quality point clouds collected by mobile LiDAR mapping systems (MLMS) provide an opportunity for effective monitoring of roadside ditches and performing hydrological analyses. This study evaluated the applicability of mobile LiDAR for mapping roadside ditches for slope and drainage analyses. The performance of alternative MLMS units was performed. These MLMS included an unmanned ground vehicle, an unmanned aerial vehicle, a portable backpack system along with its vehicle-mounted version, a medium-grade wheel-based system, and a high-grade wheel-based system. Point cloud from all the MLMS units were in agreement in the vertical direction within the ±3 cm range for solid surfaces, such as paved roads, and ±7 cm range for surfaces with vegetation. The portable backpack system that could be carried by a surveyor or mounted on a vehicle and was the most flexible MLMS. The report concludes that due to flexibility and cost effectiveness of the portable backpack system, it is the preferred platform for mapping roadside ditches, followed by the medium-grade wheel-based system. Furthermore, a framework for ditch line characterization is proposed and tested using datasets acquired by the medium-grade wheel-based and vehicle-mounted portable systems over a state highway. An existing ground filtering approach is modified to handle variations in point density of mobile LiDAR data. Hydrological analyses, including flow direction and flow accumulation, are applied to extract the drainage network from the digital terrain model (DTM). Cross-sectional/longitudinal profiles of the ditch are automatically extracted from LiDAR data and visualized in 3D point clouds and 2D images. The slope derived from the LiDAR data was found to be very close to highway cross slope design standards of 2% on driving lanes, 4% on shoulders, as well as 6-by-1 slope for ditch lines. Potential flooded regions are identified by detecting areas with no LiDAR return and a recall score of 54% and 92% was achieved by the medium-grade wheel-based and vehicle-mounted portable systems, respectively. Furthermore, a framework for ditch line characterization is proposed and tested using datasets acquired by the medium-grade wheel-based and vehicle-mounted portable systems over a state highway. An existing ground filtering approach is modified to handle variations in point density of mobile LiDAR data. Hydrological analyses, including flow direction and flow accumulation, are applied to extract the drainage network from the digital terrain model (DTM). Cross-sectional/longitudinal profiles of the ditch are automatically extracted from LiDAR data, and visualized in 3D point clouds and 2D images. The slope derived from the LiDAR data was found to be very close to highway cross slope design standards of 2% on driving lanes, 4% on shoulder, as well as 6-by-1 slope for ditch lines. Potential flooded regions are identified by detecting areas with no LiDAR return and a recall score of 54% and 92% was achieved by the medium-grade wheel-based and vehicle-mounted portable systems, respectively.
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic '3D point cloud modeling' for particular source types:
Journal articles Dissertations / Theses
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography