scholarly journals Automatic Indoor Reconstruction from Point Clouds in Multi-room Environments with Curved Walls

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3798 ◽  
Author(s):  
Fan Yang ◽  
Gang Zhou ◽  
Fei Su ◽  
Xinkai Zuo ◽  
Lei Tang ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Rapid Development ◽  
Point Clouds ◽  
Indoor Environments ◽  
Reconstruction Methods ◽  
Straight Line ◽  
Recent Developments ◽  
A Cell ◽  
Curved Walls ◽  
Indoor Reconstruction

Recent developments in laser scanning systems have inspired substantial interest in indoor modeling. Semantically rich indoor models are required in many fields. Despite the rapid development of 3D indoor reconstruction methods for building interiors from point clouds, the indoor reconstruction of multi-room environments with curved walls is still not resolved. This study proposed a novel straight and curved line tracking method followed by a straight line test. Robust parameters are used, and a novel straight line regularization method is achieved using constrained least squares. The method constructs a cell complex with both straight lines and curved lines, and the indoor reconstruction is transformed into a labeling problem that is solved based on a novel Markov Random Field formulation. The optimal labeling is found by minimizing an energy function by applying a minimum graph cut approach. Detailed experiments were conducted, and the results indicate that the proposed method is well suited for 3D indoor modeling in multi-room indoor environments with curved walls.

scholarly journals EQUAL PROPORTION REPRODUCTION METHOD OF GROTTO BASED ON POINT CLOUD

2019 ◽  
Vol XLII-2/W15 ◽  
pp. 1215-1219
Author(s):  
P. Wei ◽  
A. Li ◽  
M. Hou ◽  
L. Zhu ◽  
D. Xu ◽  
...  
Keyword(s):  
3D Printing ◽  
Point Cloud ◽  
Laser Scanning ◽  
New Technologies ◽  
Rapid Development ◽  
Point Clouds ◽  
Equal Proportion ◽  
3D Laser Scanning ◽  
Printing Technology ◽  
3D Printing Technology

<p><strong>Abstract.</strong> The rapid development of 3D laser scanning and 3D printing technology provides new technologies and ideas for cultural relic protection and reproduction. Aiming at the requirement of equal proportional reproduction of large-scale grottoes, this paper takes the point cloud data of the 18th Cave of Yungang Grottoes obtained by 3D laser scanning as an example, and proposes a data processing and reproduction block partitioning method for equal proportion reproduction. The Cyclone, Geomagic and AutoCAD software were used to construct the 3D model of the grotto, and the 3D printing technology was used to realize the secondary design and model print. Among them, the research focuses on the modeling of massive point clouds and the method of model partitioning based on voxels. It can meet the requirements of movable and assembly while realizing the equal proportional reproduction of the whole grotto. The research results and application can be a good reference for the future grotto reproduction work.</p>

scholarly journals THE ISPRS BENCHMARK ON INDOOR MODELLING – PRELIMINARY RESULTS

2020 ◽  
Vol XLIII-B5-2020 ◽  
pp. 207-211
Author(s):  
K. Khoshelham ◽  
H. Tran ◽  
D. Acharya ◽  
L. Díaz Vilariño ◽  
Z. Kang ◽  
...  
Keyword(s):  
Comprehensive Evaluation ◽  
Point Clouds ◽  
Group Iv ◽  
Evaluation Framework ◽  
Indoor Environments ◽  
Preliminary Results ◽  
Reconstruction Methods ◽  
Public Dataset ◽  
Geometric Quality ◽  
Modelling Methods

Abstract. Automated 3D reconstruction of indoor environments from point clouds has been a topic of intensive research in recent years. Different methods developed for the generation of 3D indoor models have achieved promising results on different case studies. However, a comprehensive evaluation and comparison of the performance of these methods has not been available. This paper presents the preliminary results of the ISPRS benchmark on indoor modelling, an initiative of Working Group IV/5 to benchmark the performance of indoor modelling methods using a public dataset and a comprehensive evaluation framework. The performances of the different methods are compared through geometric quality evaluation of the reconstructed models in terms of completeness, correctness, and accuracy of wall elements. The results show that the reconstruction methods generally achieve high completeness but lower correctness for the reconstructed models while accuracies range from 0.5 cm to 6.7 cm.

scholarly journals PROGRESS ON ISPRS BENCHMARK ON MULTISENSORY INDOOR MAPPING AND POSITIONING

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 1709-1713
Author(s):  
C. Wang ◽  
Y. Dai ◽  
N. El-Sheimy ◽  
C. Wen ◽  
G. Retscher ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Laser Scanning ◽  
Low Cost ◽  
Point Clouds ◽  
Indoor Positioning ◽  
Benchmark Dataset ◽  
Scanning System ◽  
Indoor Environments ◽  
Building Management ◽  
Common Framework

<p><strong>Abstract.</strong> This paper presents the design of the benchmark dataset on multisensory indoor mapping and position (MIMAP) which is sponsored by ISPRS scientific initiatives. The benchmark dataset including point clouds captured by indoor mobile laser scanning system (IMLS) in indoor environments of various complexity. The benchmark aims to stimulate and promote research in the following three fields: (1) SLAM-based indoor point cloud generation; (2) automated BIM feature extraction from point clouds, with an emphasis on the elements, such as floors, walls, ceilings, doors, windows, stairs, lamps, switches, air outlets, that are involved in building management and navigation tasks ; and (3) low-cost multisensory indoor positioning, focusing on the smartphone platform solution. MIMAP provides a common framework for the evaluation and comparison of LiDAR-based SLAM, BIM feature extraction, and smartphone indoor positioning methods.</p>

scholarly journals CHALLENGES IN FLYING QUADROTOR UNMANNED AERIAL VEHICLE FOR 3D INDOOR RECONSTRUCTION

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 423-430 ◽  
Author(s):  
J. Yan ◽  
N. Grasso ◽  
S. Zlatanova ◽  
R. C. Braggaar ◽  
D. B. Marx
Keyword(s):  
Three Dimensional ◽  
Point Clouds ◽  
3D Models ◽  
Emergency Evacuation ◽  
Vital Role ◽  
Indoor Environments ◽  
3D Tracking ◽  
High Dependency ◽  
Indoor Reconstruction

Three-dimensional modelling plays a vital role in indoor 3D tracking, navigation, guidance and emergency evacuation. Reconstruction of indoor 3D models is still problematic, in part, because indoor spaces provide challenges less-documented than their outdoor counterparts. Challenges include obstacles curtailing image and point cloud capture, restricted accessibility and a wide array of indoor objects, each with unique semantics. Reconstruction of indoor environments can be achieved through a photogrammetric approach, e.g. by using image frames, aligned using recurring corresponding image points (CIP) to build coloured point clouds. Our experiments were conducted by flying a QUAV in three indoor environments and later reconstructing 3D models which were analysed under different conditions. Point clouds and meshes were created using Agisoft PhotoScan Professional. We concentrated on flight paths from two vantage points: 1) safety and security while flying indoors and 2) data collection needed for reconstruction of 3D models. We surmised that the main challenges in providing safe flight paths are related to the physical configuration of indoor environments, privacy issues, the presence of people and light conditions. We observed that the quality of recorded video used for 3D reconstruction has a high dependency on surface materials, wall textures and object types being reconstructed. Our results show that 3D indoor reconstruction predicated on video capture using a QUAV is indeed feasible, but close attention should be paid to flight paths and conditions ultimately influencing the quality of 3D models. Moreover, it should be decided in advance which objects need to be reconstructed, e.g. bare rooms or detailed furniture.

scholarly journals THE ASSESSMENT OF CURVED CENTERLINE GENERATION IN HDMAPS BASED ON POINT CLOUDS

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 285-290
Author(s):  
J. C. Zeng ◽  
K. W. Chiang
Keyword(s):  
Laser Scanning ◽  
Road Traffic ◽  
Rapid Development ◽  
Point Clouds ◽  
Horizontal Direction ◽  
Traffic Information ◽  
Large Field ◽  
High Definition ◽  
3D Space ◽  
Lane Line

Abstract. Over the decades, autonomous driving technology has attracted a lot of attention and is under rapid development. However, it still suffers from inadequate accuracy in a certain area, such as the urban area, Global Navigation Satellite System (GNSS) hostile area, due to the multipath interference or Non-Line-of-Sight (NLOS) reception. In order to realize fully autonomous applications, High Definition Maps (HD Maps) become extra assisted information for autonomous vehicles to improve road safety in recent years. Compared with the conventional navigation maps, the accuracy requirement in HD Maps, which is 20 cm in the horizontal direction and 30 cm in 3D space, is considerably higher than the conventional one. Additionally, HD Maps consist of rich and high accurate road traffic information and road elements. For the requirement of high accuracy, conducting a Mobile Laser Scanning (MLS) system is an appropriate method to collect the geospatial data accurately and efficiently. Nowadays, digital vector maps are constructed by digitalizing manually on the collected data. However, the manual process spends a lot of manpower and is not efficient and practical for a large field. Therefore, this paper proposes to automatically construct the crucial road elements, such as road edge, lane line, and centerline, to generate the HD Maps based on point clouds collected by the MMS from the surveying company. The RMSEs in the horizontal direction of the road edge, lane line, and centerline are all lower than 30 cm in 3D space.

scholarly journals DETECTION OF INDOOR ATTACHED EQUIPMENT FROM TLS POINT CLOUDS USING PLANAR REGION BOUNDARY

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 495-500
Author(s):  
H. Takahashi ◽  
H. Date ◽  
S. Kanai ◽  
K. Yasutake
Keyword(s):  
Laser Scanning ◽  
Detection Method ◽  
Three Dimensional ◽  
Point Clouds ◽  
Indoor Environments ◽  
Base Surface ◽  
Shape Fitting ◽  
Boundary Points ◽  
Adaptive Parameters ◽  
Three Dimensional Models

Abstract. Laser scanning technology is useful to create accurate three-dimensional models of indoor environments for applications such as maintenance, inspection, renovation, and simulations. In this paper, a detection method of indoor attached equipment such as windows, lightings, and fire alarms, from TLS point clouds, is proposed. In order to make the method robust against to the lack of points of equipment surface, a footprint of the equipment is used for detection, because the entire or a part of the footprint boundary shapes explicitly appear as the boundary of base surfaces, i.e. walls for windows, and ceilings for lightings and fire alarms. In the method, first, base surface regions are extracted from given TLS point clouds of indoor environments. Then, footprint boundary points are detected from the region boundary points. Finally, target equipment is detected by fitting or voting using given target footprint shapes. The features of our method are footprint boundary point extraction considering occlusions, shape fitting with adaptive parameters based on point intervals, and robust shape detection by voting from multiple footprint boundary candidates. The effectiveness of the proposed method is evaluated using TLS point clouds.

scholarly journals WebGL Visualisation of 3D Environmental Models Based on Finnish Open Geospatial Data Sets

2014 ◽  
Vol XL-3 ◽  
pp. 163-169 ◽  
Author(s):  
A. Krooks ◽  
J. Kahkonen ◽  
L. Lehto ◽  
P. Latvala ◽  
M. Karjalainen ◽  
...  
Keyword(s):  
Spatial Data ◽  
Laser Scanning ◽  
National Level ◽  
Image Data ◽  
Point Clouds ◽  
Open Pit ◽  
Data Sets ◽  
Environmental Models ◽  
3D City Model ◽  
Recent Developments

Recent developments in spatial data infrastructures have enabled real time GIS analysis and visualization using open input data sources and service interfaces. In this study we present a new concept where metric point clouds derived from national open airborne laser scanning (ALS) and photogrammetric image data are processed, analyzed, finally visualised a through open service interfaces to produce user-driven analysis products from targeted areas. The concept is demonstrated in three environmental applications: assessment of forest storm damages, assessment of volumetric changes in open pit mine and 3D city model visualization. One of the main objectives was to study the usability and requirements of national level photogrammetric imagery in these applications. The results demonstrated that user driven 3D geospatial analyses were possible with the proposed approach and current technology, for instance, the landowner could assess the amount of fallen trees within his property borders after a storm easily using any web browser. On the other hand, our study indicated that there are still many uncertainties especially due to the insufficient standardization of photogrammetric products and processes and their quality indicators.

scholarly journals ISPRS BENCHMARK ON MULTISENSORY INDOOR MAPPING AND POSITIONING

2020 ◽  
Vol V-5-2020 ◽  
pp. 117-123
Author(s):  
C. Wang ◽  
Y. Dai ◽  
N. Elsheimy ◽  
C. Wen ◽  
G. Retscher ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Laser Scanning ◽  
Point Clouds ◽  
Indoor Positioning ◽  
Benchmark Dataset ◽  
Scanning System ◽  
Indoor Environments ◽  
Process Data ◽  
Localization And Mapping ◽  
Common Framework

Abstract. In this paper, we present a publicly available benchmark dataset on multisensorial indoor mapping and positioning (MiMAP), which is sponsored by ISPRS scientific initiatives. The benchmark dataset includes point clouds captured by an indoor mobile laser scanning system in indoor environments of various complexity. The benchmark aims to stimulate and promote research in the following three fields: (1) LiDAR-based Simultaneous Localization and Mapping (SLAM); (2) automated Building Information Model (BIM) feature extraction; and (3) multisensory indoor positioning. The MiMAP project provides a common framework for the evaluation and comparison of LiDAR-based SLAM, BIM feature extraction, and smartphone-based indoor positioning methods. This paper describes the multisensory setup, data acquisition process, data description, challenges, and evaluation metrics included in the MiMAP project.

scholarly journals AUTOMATIC EXTRACTION OF A NAVIGATION GRAPH INTENDED FOR INDOORGML FROM AN INDOOR POINT CLOUD

2019 ◽  
Vol IV-2/W5 ◽  
pp. 271-278
Author(s):  
P. Flikweert ◽  
R. Peters ◽  
L. Díaz-Vilariño ◽  
R. Voûte ◽  
B. Staats
Keyword(s):  
Laser Scanning ◽  
Medial Axis ◽  
Laser Scanner ◽  
Point Clouds ◽  
Essential Elements ◽  
Indoor Navigation ◽  
Indoor Environments ◽  
Architectural Drawings ◽  
The Public ◽  
First Results

<p><strong>Abstract.</strong> Indoor environments tend to be more complex and more populated when buildings are accessible to the public. The need for knowing where people are, how they can get somewhere or how to reach them in these buildings is thus equally increasing. In this research point clouds are used, obtained by dynamic laser scanning of a building, since we cannot rely on architectural drawings for maps and paths, which can be outdated. The presented method focuses on the creation of an indoor navigation graph, based on IndoorGML structure, in a fast and automated way, while retaining the type of walkable surface. In this paper the focus has been on door detection, because doors are essential elements in an indoor environment, seeing that they connect spaces and are a logical step in a route. This paper describes a way to detect doors using 3D Medial Axis Transform (MAT) combined with the intelligence stored in the path of a mobile laser scanner, showing good first results. Additionally different spaces (e.g. rooms and corridors) in the building are identified and slopes and stairs in walkable spaces are detected. This results in a navigation graph which can be stored in an IndoorGML structure.</p>

scholarly journals LINE SEGMENTATION OF 2D LASER SCANNER POINT CLOUDS FOR INDOOR SLAM BASED ON A RANGE OF RESIDUALS

2017 ◽  
Vol IV-2/W4 ◽  
pp. 363-369 ◽  
Author(s):  
M. Peter ◽  
S. R. U. N. Jafri ◽  
G. Vosselman
Keyword(s):  
Laser Scanning ◽  
Degrees Of Freedom ◽  
Large Scale ◽  
Laser Scanner ◽  
Point Clouds ◽  
Indoor Environments ◽  
Six Degrees Of Freedom ◽  
Localization And Mapping ◽  
Feature Based ◽  
Definition Of

Indoor mobile laser scanning (IMLS) based on the Simultaneous Localization and Mapping (SLAM) principle proves to be the preferred method to acquire data of indoor environments at a large scale. In previous work, we proposed a backpack IMLS system containing three 2D laser scanners and an according SLAM approach. The feature-based SLAM approach solves all six degrees of freedom simultaneously and builds on the association of lines to planes. Because of the iterative character of the SLAM process, the quality and reliability of the segmentation of linear segments in the scanlines plays a crucial role in the quality of the derived poses and consequently the point clouds. The orientations of the lines resulting from the segmentation can be influenced negatively by narrow objects which are nearly coplanar with walls (like e.g. doors) which will cause the line to be tilted if those objects are not detected as separate segments. State-of-the-art methods from the robotics domain like Iterative End Point Fit and Line Tracking were found to not handle such situations well. Thus, we describe a novel segmentation method based on the comparison of a range of residuals to a range of thresholds. For the definition of the thresholds we employ the fact that the expected value for the average of residuals of <i>n</i> points with respect to the line is <i>σ</i>&amp;thinsp;/&amp;thinsp;&amp;radic;<i>n</i>. Our method, as shown by the experiments and the comparison to other methods, is able to deliver more accurate results than the two approaches it was tested against.

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