Registration of Point-Clouds from Terrestrial and Portable Laser Scanners

2016 ◽  
Vol 10 (2) ◽  
pp. 163-171 ◽  
Author(s):  
Takuma Watanabe ◽  
◽  
Takeru Niwa ◽  
Hiroshi Masuda ◽  
Keyword(s):  
Point Cloud ◽  
Short Range ◽  
Large Scale ◽  
Laser Scanner ◽  
Point Clouds ◽  
Limited Region ◽  
Registration Method ◽  
Laser Scanners ◽  
Scale Point ◽  
Candidate Regions

We proposed a registration method for aligning short-range point-clouds captured using a portable laser scanner (PLS) to a large-scale point-cloud captured using a terrestrial laser scanner (TLS). As a PLS covers a very limited region, it often fails to provide sufficient features for registration. In our method, the system analyzes large-scale point-clouds captured using a TLS and indicates candidate regions to be measured using a PLS. When the user measures a suggested region, the system aligns the captured short-range point-cloud to the large-scale point-cloud. Our experiments show that the registration method can adequately align point-clouds captured using a TLS and a PLS.

Special Issue on Large-Scale Point Cloud Processing

2018 ◽  
Vol 12 (3) ◽  
pp. 327-327
Author(s):  
Hiroshi Masuda ◽  
Hiroaki Date
Keyword(s):  
Point Cloud ◽  
Large Scale ◽  
Point Clouds ◽  
Special Issue ◽  
New Techniques ◽  
Accuracy Measurement ◽  
Cloud Processing ◽  
Point Cloud Processing ◽  
Laser Scanners ◽  
Scale Point

Recently, terrestrial laser scanners have been significantly improved in terms of accuracy, measurement distance, measurement speed, and resolution. They enable us to capture dense 3D point clouds of large-scale objects and fields, such as factories, engineering plants, large equipment, and transport ships. In addition, the mobile mapping system, which is a vehicle equipped with laser scanners and GPSs, can be used for capturing large-scale point clouds from a wide range of roads, buildings, and roadside objects. Large-scale point clouds are useful in a variety of applications, such as renovation and maintenance of facilities, engineering simulation, asset management, and 3D mapping. To realize these applications, new techniques must be developed for processing large-scale point clouds. So far, point processing has been studied mainly for relatively small objects in the field of computer-aided design and computer graphics. However, in recent years, the application areas of point clouds are not limited to conventional domains, but also include manufacturing, civil engineering, construction, transportation, forestry, and so on. This is because the state-of-the-art laser scanner can be used to represent large objects or fields as dense point clouds. We believe that discussing new techniques and applications related to large-scale point clouds beyond the boundaries of traditional academic fields is very important.This special issue addresses the latest research advances in large-scale point cloud processing. This covers a wide area of point processing, including shape reconstruction, geometry processing, object recognition, registration, visualization, and applications. The papers will help readers explore and share their knowledge and experience in technologies and development techniques.All papers were refereed through careful peer reviews. We would like to express our sincere appreciation to the authors for their submissions and to the reviewers for their invaluable efforts for ensuring the success of this special issue.

scholarly journals A REGISTRATION METHOD OF POINT CLOUDS COLLECTED BY MOBILE LIDAR USING SOLELY STANDARD LAS FILES INFORMATION

2017 ◽  
Vol XLII-1/W1 ◽  
pp. 121-128 ◽  
Author(s):  
L. Gézero ◽  
C. Antunes
Keyword(s):  
Point Cloud ◽  
Large Scale ◽  
Auxiliary Information ◽  
Point Clouds ◽  
Registration Method ◽  
Digital Terrain ◽  
Terrain Models ◽  
Dense Point ◽  
Fully Automatic ◽  
Method Point

In the last few years, LiDAR sensors installed in terrestrial vehicles have been revealed as an efficient method to collect very dense 3D georeferenced information. The possibility of creating very dense point clouds representing the surface surrounding the sensor, at a given moment, in a very fast, detailed and easy way, shows the potential of this technology to be used for cartography and digital terrain models production in large scale. However, there are still some limitations associated with the use of this technology. When several acquisitions of the same area with the same device, are made, differences between the clouds can be observed. The range of that differences can go from few centimetres to some several tens of centimetres, mainly in urban and high vegetation areas where the occultation of the GNSS system introduces a degradation of the georeferenced trajectory. Along this article a different method point cloud registration is proposed. In addition to the efficiency and speed of execution, the main advantages of the method are related to the fact that the adjustment is continuously made over the trajectory, based on the GPS time. The process is fully automatic and only information recorded in the standard LAS files is used, without the need for any auxiliary information, in particular regarding the trajectory.

A Point-Based Virtual Reality System for Supporting Product Development

2016 ◽  
Author(s):  
Hiroki Okamoto ◽  
Hiroshi Masuda
Keyword(s):  
Product Development ◽  
Large Scale ◽  
Point Clouds ◽  
Visible Points ◽  
Laser Scanners ◽  
Angle Space ◽  
Panoramic Images ◽  
Scale Point ◽  
Development Phases ◽  
Short Time

In this paper, we discuss methods to efficiently render stereoscopic scenes of large-scale point-clouds on inexpensive VR systems. Recently, terrestrial laser scanners are significantly improved, and they can easily capture tens of millions points in a short time from large fields, such as engineering plants. If 3D stereoscopic scenes of large-scale point-clouds could be easily rendered using inexpensive devices, they might be involved in casual product development phases. However, it is difficult to render a huge number of points using common PCs, because VR systems require high frame rates to avoid VR sickness. To solve this problem, we introduce an efficient culling method for large-scale point-clouds. In our method, we project all points onto angle-space panoramic images, whose axes are the azimuth and elevation angles of head directions. Then we eliminate occluded and redundant points according to the resolutions of devices. Once visible points are selected, they can be rendered in high frame rates. Visible points are updated when the user stays at a certain position to observe target objects. Since points are processed on image space in our method, preprocessing is very fast. In our experiments, our method could render stereoscopic views of large-scale point-clouds in high frame rates.

Detection of Surfaces and Edges in Large Point-Clouds Using Region-Growing on Spherical Space

2012 ◽  
Vol 523-524 ◽  
pp. 333-338
Author(s):  
Hiroshi Masuda ◽  
Ryo Matsuoka ◽  
Yuji Abe
Keyword(s):  
Large Scale ◽  
Region Growing ◽  
Point Clouds ◽  
The State ◽  
Spherical Space ◽  
Parametric Surfaces ◽  
Cad Systems ◽  
Laser Scanners ◽  
Scale Point ◽  
State Of Art

Engineering facilities can be digitized as large-scale point-clouds by using the state-of-art mid-range laser scanners. For utilizing captured data in CAD systems, it is important to convert point-clouds to parametric surfaces. In this paper, we describe a method for robustly extract cylindrical faces and planar faces. Edges and silhouette lines have to be generated to construct bounded faces, but unfortunately points on silhouettes are very noisy in the case of mid-range laser scanners. Our method applies region-growing method on spherical space and improves the robustness. In addition, we enhance the region-growing so that surface regions can be propagated to disconnect points using multiple overlapping point-clouds.

scholarly journals Reconstruction of polygonal prisms from point-clouds of engineering facilities

2016 ◽  
Vol 3 (4) ◽  
pp. 322-329 ◽  
Author(s):  
Akisato Chida ◽  
Hiroshi Masuda
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Point Clouds ◽  
Reconstruction Method ◽  
Shape Acquisition ◽  
Laser Scanners ◽  
Dense Point ◽  
Scale Point ◽  
3D Shape Acquisition ◽  
Actual Point

Abstract The advent of high-performance terrestrial laser scanners has made it possible to capture dense point-clouds of engineering facilities. 3D shape acquisition from engineering facilities is useful for supporting maintenance and repair tasks. In this paper, we discuss methods to reconstruct box shapes and polygonal prisms from large-scale point-clouds. Since many faces may be partly occluded by other objects in engineering plants, we estimate possible box shapes and polygonal prisms and verify their compatibility with measured point-clouds. We evaluate our method using actual point-clouds of engineering plants. Highlights This paper proposes a point-based reconstruction method for boxes and polygonal prisms in engineering plants. Many faces may be partly occluded by other objects in engineering plants. In our method, possible shapes are estimated and they are verified using their compatibility with measured point-clouds. In our experiments, our method achieved high precision and recall rates.

scholarly journals OPACITY-BASED EDGE HIGHLIGHTING FOR TRANSPARENT VISUALIZATION OF 3D SCANNED POINT CLOUDS

2020 ◽  
Vol V-2-2020 ◽  
pp. 373-380
Author(s):  
K. Kawakami ◽  
K. Hasegawa ◽  
L. Li ◽  
H. Nagata ◽  
M. Adachi ◽  
...  
Keyword(s):  
Real World ◽  
Point Cloud ◽  
Large Scale ◽  
3D Structure ◽  
Point Clouds ◽  
High Quality ◽  
3D Images ◽  
3D Structures ◽  
3D Objects ◽  
Scale Point

Abstract. The recent development of 3D scanning technologies has made it possible to quickly and accurately record various 3D objects in the real world. The 3D scanned data take the form of large-scale point clouds, which describe complex 3D structures of the target objects and the surrounding scenes. The complexity becomes significant in cases that a scanned object has internal 3D structures, and the acquired point cloud is created by merging the scanning results of both the interior and surface shapes. To observe the whole 3D structure of such complex point-based objects, the point-based transparent visualization, which we recently proposed, is useful because we can observe the internal 3D structures as well as the surface shapes based on high-quality see-through 3D images. However, transparent visualization sometimes shows us too much information so that the generated images become confusing. To address this problem, in this paper, we propose to combine “edge highlighting” with transparent visualization. This combination makes the created see-through images quite understandable because we can highlight the 3D edges of visualized shapes as high-curvature areas. In addition, to make the combination more effective, we propose a new edge highlighting method applicable to 3D scanned point clouds. We call the method “opacity-based edge highlighting,” which appropriately utilizes the effect of transparency to make the 3D edge regions look clearer. The proposed method works well for both sharp (high-curvature) and soft (low-curvature) 3D edges. We show several experiments that demonstrate our method’s effectiveness by using real 3D scanned point clouds.

scholarly journals Application of 3D Laser Scanning for Digitization, Design and Analysis of Multistoried Building

2021 ◽  
Author(s):  
Abdul Qadir Bhatti ◽  
◽  
Abdul Wahab ◽  
Wadea Sindi ◽  
◽  
...  
Keyword(s):  
Structural Damage ◽  
Point Cloud ◽  
Laser Scanning ◽  
Passive Control ◽  
Complex Geometry ◽  
Laser Scanner ◽  
Point Clouds ◽  
Historical Building ◽  
Laser Scanners ◽  
Original Construction

Laser scanning is a fast-developing technology, which collects millions of points and creates a framework within a few minutes, generating a 'point cloud' of the structure. Laser scanning is a quite new but rapidly evolving technology that has been reviewed. this research study has used most modern models of laser scanners and their accompanying software that are capable of accurate capture and alignment of point clouds. Consequently, the laser scans have precisely captured the current geometry of each structure, which is irregular in many cases due to inherently complex geometry, anomalies during the original construction, aging, deterioration, and structural damage. As both the exterior and interior of the structure have been scanned, the point cloud became a digital 3D image of the historical building, which can be virtually toured from inside and outside. A 4-story public building was scanned using a 3D laser scanner to determine the architectural and structural drawings of the response to an earthquake. The application of passive control using a damper with the laser scanner has been modelled in this study. The results corroborate that this technique provides the best outcomes for reducing seismic damage collapses.

scholarly journals SEE-THROUGH IMAGING OF LASER-SCANNED 3D CULTURAL HERITAGE OBJECTS BASED ON STOCHASTIC RENDERING OF LARGE-SCALE POINT CLOUDS

2016 ◽  
Vol III-5 ◽  
pp. 73-80 ◽  
Author(s):  
S. Tanaka ◽  
K. Hasegawa ◽  
N. Okamoto ◽  
R. Umegaki ◽  
S. Wang ◽  
...  
Keyword(s):  
Cultural Heritage ◽  
Laser Scanning ◽  
Large Scale ◽  
Laser Scanner ◽  
Point Clouds ◽  
Cultural Value ◽  
Stochastic Algorithm ◽  
Scale Point ◽  
3D Scene ◽  
Cultural Heritage Objects

We propose a method for the precise 3D see-through imaging, or transparent visualization, of the large-scale and complex point clouds acquired via the laser scanning of 3D cultural heritage objects. Our method is based on a stochastic algorithm and directly uses the 3D points, which are acquired using a laser scanner, as the rendering primitives. This method achieves the correct depth feel without requiring depth sorting of the rendering primitives along the line of sight. Eliminating this need allows us to avoid long computation times when creating natural and precise 3D see-through views of laser-scanned cultural heritage objects. The opacity of each laser-scanned object is also flexibly controllable. For a laser-scanned point cloud consisting of more than 10<sup>7</sup> or 10<sup>8</sup> 3D points, the pre-processing requires only a few minutes, and the rendering can be executed at interactive frame rates. Our method enables the creation of cumulative 3D see-through images of time-series laser-scanned data. It also offers the possibility of fused visualization for observing a laser-scanned object behind a transparent high-quality photographic image placed in the 3D scene. We demonstrate the effectiveness of our method by applying it to festival floats of high cultural value. These festival floats have complex outer and inner 3D structures and are suitable for see-through imaging.

scholarly journals Semantic Interpretation of Mobile Laser Scanner Point Clouds in Indoor Scenes Using Trajectories

2018 ◽  
Vol 10 (11) ◽  
pp. 1754 ◽  
Author(s):  
Shayan Nikoohemat ◽  
Michael Peter ◽  
Sander Oude Elberink ◽  
George Vosselman
Keyword(s):  
3D Modeling ◽  
Point Cloud ◽  
Essential Role ◽  
Low Cost ◽  
Laser Scanner ◽  
Point Clouds ◽  
Semantic Interpretation ◽  
Adjacency Graph ◽  
Laser Scanners ◽  
Indoor Scenes

The data acquisition with Indoor Mobile Laser Scanners (IMLS) is quick, low-cost and accurate for indoor 3D modeling. Besides a point cloud, an IMLS also provides the trajectory of the mobile scanner. We analyze this trajectory jointly with the point cloud to support the labeling of noisy, highly reflected and cluttered points in indoor scenes. An adjacency-graph-based method is presented for detecting and labeling of permanent structures, such as walls, floors, ceilings, and stairs. Through occlusion reasoning and the use of the trajectory as a set of scanner positions, gaps are discriminated from real openings in the data. Furthermore, a voxel-based method is applied for labeling of navigable space and separating them from obstacles. The results show that 80% of the doors and 85% of the rooms are correctly detected, and most of the walls and openings are reconstructed. The experimental outcomes indicate that the trajectory of MLS systems plays an essential role in the understanding of indoor scenes.

scholarly journals Fused Transparent Visualization of Point Cloud Data and Background Photographic Image for Tangible Cultural Heritage Assets

2019 ◽  
Vol 8 (8) ◽  
pp. 343 ◽  
Author(s):  
Li ◽  
Hasegawa ◽  
Nii ◽  
Tanaka
Keyword(s):  
Cultural Heritage ◽  
Point Cloud ◽  
Laser Scanning ◽  
Large Scale ◽  
Three Dimensional ◽  
Point Clouds ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Photographic Image ◽  
Scale Point

Digital archiving of three-dimensional cultural heritage assets has increased the demand for visualization of large-scale point clouds of cultural heritage assets acquired by laser scanning. We proposed a fused transparent visualization method that visualizes a point cloud of a cultural heritage asset in an environment using a photographic image as the background. We also proposed lightness adjustment and color enhancement methods to deal with the reduced visibility caused by the fused visualization. We applied the proposed method to a laser-scanned point cloud of a high-valued cultural festival float with complex inner and outer structures. Experimental results demonstrate that the proposed method enables high-quality transparent visualization of the cultural asset in its surrounding environment.

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