scholarly journals evaluation of intensity augmented ICP for terrestrial LiDAR data registration

2018 ◽  
Author(s):  
Sandeep Sasidharan
Keyword(s):  
Laser Scanner ◽  
Point Clouds ◽  
3D Models ◽  
Accurate Estimation ◽  
Lidar Data ◽  
Terrestrial Lidar ◽  
Data Registration ◽  
Novel Approach ◽  
Coarse Registration ◽  
Scan Registration

Final pub: Lohani, B., & Sasidharan, S. (2017). An evaluation of intensity augmented ICP for terrestrial LiDAR data registration. Journal of Geomatics, 11(2). While using laser scanner for map-making or developing 3D models of objects, it is important to scan asite or an object from multiple viewpoints. These different scans are integrated to generate a complete point cloudwhich is then used for developing the map or 3D model of the site. ICP (Iterative Closest Point) is a standard algorithmfor registration of point clouds. However, in the absence of marked features which are geometrically distinct in thepoint clouds, which are being combined, this method sometime fails. This paper exploits the radiometric data that arealways obtained along with the coordinates and devises a novel approach for scan registration. Before usingradiometric data in registration process, the data are normalized. The algorithm presented in this paper works in twostages- Intensity Augmented ICP (IAICP) for coarse registration stage and conventional geometric ICP at the fineregistration stage. The proposed approach is successfully applied to a few test data captured by Optech ILRIS 36-Dresulting in an accurate estimation of the transformation parameters. A comparison of the conventional and intensityaugmented registration approaches is also presented. The results indicate the supremacy of IAICP over the ICP, as thelatter is found to fail in geometrically confusing cases while the intensity augmented ICP gives satisfactory result insuch cases.

scholarly journals THE COMBINATION OF TERRESTRIAL LIDAR AND UAV PHOTOGRAMMETRY FOR INTERACTIVE ARCHITECTURAL HERITAGE VISUALIZATION USING UNITY 3D GAME ENGINE

2019 ◽  
Vol XLII-2/W17 ◽  
pp. 39-44
Author(s):  
R. Andaru ◽  
B. K. Cahyono ◽  
G. Riyadi ◽  
G. R. Ramadhan ◽  
S. Tuntas ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Laser Scanner ◽  
Point Clouds ◽  
3D Models ◽  
High Density ◽  
Game Engine ◽  
Architectural Heritage ◽  
Terrestrial Lidar ◽  
Heritage Building ◽  
Software Modelling

Abstract. The digital 3D documentation of architectural heritage using advanced 3D measurement technologies such as UAV photogrammetry and terrestrial LiDAR (TLS) becomes a potential and efficient method since it can produce 3D pointclouds in detail and high density of pointclouds levels. However, TLS is unable to scan the roof part of tall building, whereas UAV photogrammetry achieves high density of pointclouds at that area. In order to make a complete 3D pointclouds of heritage building, we merged and integrated the TLS and UAV pointclouds data by using Iterative Closest Point (ICP) algorithms into one reference system. In this study, we collected two architectural heritage building in Yogyakarta, Indonesia, i.e., "Vredeburg Fort Museum (VFM)" and "Kotagede Great Mosque (KGM)", the oldest mosque in Yogyakarta. For the data acquisition, we used Faro Focus X330 and GLS 2000 Laser Scanner. We produced three-dimensional point clouds from UAV imagery by using Structure from Motion and Multi View Stereo (SfM-MVS) technique through Photoscan software. In order to merging and integrating both of pointclouds data, Maptek I-Site Studio 6.1 with Educational License was used. Those data were successfully registered, and according to the registration report, we had observed 20.60 mm of RMS error. The 3D models and their textures in outdoor and indoor side were processed using Autodesk software. Modelling was carried out on the structure of building’s façade base on simple geometric primitive as planes, straight lines, circles, spheres and cylinder. For interactive visualization, a modern and widely accessible game engine technology (Unity3D) was used. The result was an interactive displaying 3D model of an architectural heritage building in LOD3 level with spatial function for measuring the size and dimension, as well as the area of object. Finally, we created the online version of interactive 3D viewer utilizing WebGL API and Mapbox Unity SDK.

scholarly journals Localization in Unstructured Environments: Towards Autonomous Robots in Forests with Delaunay Triangulation

2020 ◽  
Vol 12 (11) ◽  
pp. 1870 ◽  
Author(s):  
Qingqing Li ◽  
Paavo Nevalainen ◽  
Jorge Peña Queralta ◽  
Jukka Heikkonen ◽  
Tomi Westerlund
Keyword(s):  
Autonomous Robots ◽  
Laser Scanner ◽  
Point Clouds ◽  
Time Data ◽  
Unstructured Environments ◽  
Accurate Localization ◽  
Novel Approach ◽  
Local Point ◽  
Feature Based ◽  
Real Time Data Processing

Autonomous harvesting and transportation is a long-term goal of the forest industry. One of the main challenges is the accurate localization of both vehicles and trees in a forest. Forests are unstructured environments where it is difficult to find a group of significant landmarks for current fast feature-based place recognition algorithms. This paper proposes a novel approach where local point clouds are matched to a global tree map using the Delaunay triangularization as the representation format. Instead of point cloud based matching methods, we utilize a topology-based method. First, tree trunk positions are registered at a prior run done by a forest harvester. Second, the resulting map is Delaunay triangularized. Third, a local submap of the autonomous robot is registered, triangularized and matched using triangular similarity maximization to estimate the position of the robot. We test our method on a dataset accumulated from a forestry site at Lieksa, Finland. A total length of 200 m of harvester path was recorded by an industrial harvester with a 3D laser scanner and a geolocation unit fixed to the frame. Our experiments show a 12 cm s.t.d. in the location accuracy and with real-time data processing for speeds not exceeding 0.5 m/s. The accuracy and speed limit are realistic during forest operations.

scholarly journals Monitoring and Computation of the Volumes of Stockpiles of Bulk Material by Means of UAV Photogrammetric Surveying

2019 ◽  
Vol 11 (12) ◽  
pp. 1471 ◽  
Author(s):  
Grazia Tucci ◽  
Antonio Gebbia ◽  
Alessandro Conti ◽  
Lidia Fiorini ◽  
Claudio Lubello
Keyword(s):  
Bulk Material ◽  
Laser Scanner ◽  
Ground Truth ◽  
Point Clouds ◽  
3D Models ◽  
Satellite System ◽  
3D Data ◽  
Current Survey ◽  
Close Range ◽  
Global Navigation Satellite

The monitoring and metric assessment of piles of natural or man-made materials plays a fundamental role in the production and management processes of multiple activities. Over time, the monitoring techniques have undergone an evolution linked to the progress of measure and data processing techniques; starting from classic topography to global navigation satellite system (GNSS) technologies up to the current survey systems like laser scanner and close-range photogrammetry. Last-generation 3D data management software allow for the processing of increasingly truer high-resolution 3D models. This study shows the results of a test for the monitoring and computing of stockpile volumes of material coming from the differentiated waste collection inserted in the recycling chain, performed by means of an unmanned aerial vehicle (UAV) photogrammetric survey and the generation of 3D models starting from point clouds. The test was carried out with two UAV flight sessions, with vertical and oblique camera configurations, and using a terrestrial laser scanner for measuring the ground control points and as ground truth for testing the two survey configurations. The computations of the volumes were carried out using two software and comparisons were made both with reference to the different survey configurations and to the computation software.

scholarly journals Tunnel Vision

2016 ◽  
Vol 4 (2) ◽  
pp. 192-204 ◽  
Author(s):  
Thomas G. Garrison ◽  
Dustin Richmond ◽  
Perry Naughton ◽  
Eric Lo ◽  
Sabrina Trinh ◽  
...  
Keyword(s):  
3D Models ◽  
Present Form ◽  
Light Detection And Ranging ◽  
Lidar Data ◽  
Technical Expertise ◽  
Ancient Maya ◽  
Light Detection ◽  
Terrestrial Lidar ◽  
Tunnel Vision ◽  
El Zotz

AbstractArchaeological tunneling is a standard excavation strategy in Mesoamerica. The ancient Maya built new structures atop older ones that were no longer deemed usable, whether for logistical or ideological reasons. This means that as archaeologists excavate horizontal tunnels into ancient Maya structures, they are essentially moving back in time. As earlier constructions are encountered, these tunnels may deviate in many directions in order to document architectural remains. The resultant excavations often become intricate labyrinths, extending dozens of meters. Traditional forms of archaeological documentation, such as photographs, plan views, and profile drawings, are limited in their ability to convey the complexity of tunnel excavations. Terrestrial Lidar (light detection and ranging) instruments are able to generate precise 3D models of tunnel excavations. This article presents the results of a model created with a Faro™ Focus 3D 120 Scanner of tunneling excavations at the site of El Zotz, Guatemala. The lidar data document the excavations inside a large mortuary pyramid, including intricately decorated architecture from an Early Classic (A.D. 300–600) platform buried within the present form of the structure. Increased collaboration between archaeologists and scholars with technical expertise maximizes the effectiveness of 3D models, as does presenting digital results in tandem with traditional forms of documentation.

scholarly journals MULTI-SCALE BASED EXTRACION OF VEGETATION FROM TERRESTRIAL LiDAR DATA FOR ASSESSING LOCAL LANDSCAPE

2015 ◽  
Vol II-3/W4 ◽  
pp. 263-270 ◽  
Author(s):  
T. Wakita ◽  
J. Susaki
Keyword(s):  
Urban Areas ◽  
Three Dimensional ◽  
Point Clouds ◽  
Lidar Data ◽  
Data Sets ◽  
Landscape Index ◽  
Terrestrial Lidar ◽  
Multi Scale ◽  
3D Point Clouds ◽  
Set Of Points

In this study, we propose a method to accurately extract vegetation from terrestrial three-dimensional (3D) point clouds for estimating landscape index in urban areas. Extraction of vegetation in urban areas is challenging because the light returned by vegetation does not show as clear patterns as man-made objects and because urban areas may have various objects to discriminate vegetation from. The proposed method takes a multi-scale voxel approach to effectively extract different types of vegetation in complex urban areas. With two different voxel sizes, a process is repeated that calculates the eigenvalues of the planar surface using a set of points, classifies voxels using the approximate curvature of the voxel of interest derived from the eigenvalues, and examines the connectivity of the valid voxels. We applied the proposed method to two data sets measured in a residential area in Kyoto, Japan. The validation results were acceptable, with F-measures of approximately 95% and 92%. It was also demonstrated that several types of vegetation were successfully extracted by the proposed method whereas the occluded vegetation were omitted. We conclude that the proposed method is suitable for extracting vegetation in urban areas from terrestrial light detection and ranging (LiDAR) data. In future, the proposed method will be applied to mobile LiDAR data and the performance of the method against lower density of point clouds will be examined.

scholarly journals Application of modern 3d image acquisition systems to the morphological analysis of faces: a novel approach for the assessment of facial growth

2020 ◽  
Vol 7 (4) ◽  
pp. 268-273
Author(s):  
Gibelli Daniele Maria ◽  
◽  
Poppa Pasquale ◽  
Cappella Annalisa ◽  
Rosati Riccardo ◽  
...  
Keyword(s):  
Morphological Analysis ◽  
Three Dimensional ◽  
Laser Scanner ◽  
3D Models ◽  
Point Of View ◽  
Topographic Map ◽  
Facial Growth ◽  
General Increase ◽  
Novel Approach ◽  
Point To Point

Introduction The assessment of facial growth has always had a relevant importance in anatomy and morphological sciences. This article aims at presenting a method of facial superimposition between 3D models which provides a topographic map of those facial areas modified by growth. Methodology Eight children aged between 6 and 10 years were recruited. In December 2010 they underwent a 3D scan by the Vivid 910 laser scanner (Konica Minolta, Osaka, Japan). The same procedures were performed another five times, in June 2011, September 2011, January 2012 and September 2012; in total 6 analyses were performed on the same subjects in a time span of 21 months. Three-dimensional digital models belonging to the same individual were then superimposed on each other according to 11 facial landmarks. Three comparisons were performed for each individual, referring to the period between December 2010 and June 2011, between June 2011 and January 2012 and between January and September 2012. Results Results show that the protocol of superimposition gives a reliable image of facial growth with high sensibility: in detail, even the slight facial modifications due to different expressions are recorded. The method can also quantify the point-to-point difference between the two models, and therefore give an indication concerning the general increase or decrease of facial volume. Conclusion This approach may provide useful indications for the analysis of facial growth on a large sample and give a new point of view of the complex field of face development.

scholarly journals POSSIBILITIES FOR USING LIDAR AND PHOTOGRAMMETRIC DATA OBTAINED WITH AN UNMANNED AERIAL VEHICLE FOR LEVEE MONITORING

2016 ◽  
Vol XLI-B1 ◽  
pp. 773-780 ◽  
Author(s):  
K. Bakuła ◽  
W. Ostrowski ◽  
M. Szender ◽  
W. Plutecki ◽  
A. Salach ◽  
...  
Keyword(s):  
Laser Scanner ◽  
Digital Camera ◽  
Digital Terrain Model ◽  
Point Clouds ◽  
Lidar Data ◽  
Unmanned Aerial System ◽  
Navigation Systems ◽  
Control Points ◽  
Terrain Model ◽  
Increase In Accuracy

This paper presents the possibilities for using an unmanned aerial system for evaluation of the condition of levees. The unmanned aerial system is equipped with two types of sensor. One is an ultra-light laser scanner, integrated with a GNSS receiver and an INS system; the other sensor is a digital camera that acquires data with stereoscopic coverage. Sensors have been mounted on the multirotor, unmanned platform the Hawk Moth, constructed by MSP company. LiDAR data and images of levees the length of several hundred metres were acquired during testing of the platform. Flights were performed in several variants. Control points measured with the use of the GNSS technique were considered as reference data. The obtained results are presented in this paper; the methodology of processing the acquired LiDAR data, which increase in accuracy when low accuracy of the navigation systems occurs as a result of systematic errors, is also discussed. The Iterative Closest Point (ICP) algorithm, as well as measurements of control points, were used to georeference the LiDAR data. Final accuracy in the order of centimetres was obtained for generation of the digital terrain model. The final products of the proposed UAV data processing are digital elevation models, an orthophotomap and colour point clouds. The authors conclude that such a platform offers wide possibilities for low-budget flights to deliver the data, which may compete with typical direct surveying measurements performed during monitoring of such objects. However, the biggest advantage is the density and continuity of data, which allows for detection of changes in objects being monitored.

Verfahren zur Registrierung von Laserscannerdaten in Waldbeständen | Methods for registration laser scanner point clouds in forest stands

2011 ◽  
Vol 162 (6) ◽  
pp. 178-185 ◽  
Author(s):  
Anne Bienert ◽  
Katharina Pech ◽  
Hans-Gerd Maas
Keyword(s):  
Laser Scanning ◽  
Laser Scanner ◽  
Point Clouds ◽  
Forest Stand ◽  
Geometric Transformation ◽  
Complex Object ◽  
Tree Detection ◽  
Airborne Laser ◽  
Coarse Registration ◽  
Fine Registration

Laser scanning is a fast and efficient 3-D measurement technique to capture surface points describing the geometry of a complex object in an accurate and reliable way. Besides airborne laser scanning, terrestrial laser scanning finds growing interest for forestry applications. These two different recording platforms show large differences in resolution, recording area and scan viewing direction. Using both datasets for a combined point cloud analysis may yield advantages because of their largely complementary information. In this paper, methods will be presented to automatically register airborne and terrestrial laser scanner point clouds of a forest stand. In a first step, tree detection is performed in both datasets in an automatic manner. In a second step, corresponding tree positions are determined using RANSAC. Finally, the geometric transformation is performed, divided in a coarse and fine registration. After a coarse registration, the fine registration is done in an iterative manner (ICP) using the point clouds itself. The methods are tested and validated with a dataset of a forest stand. The presented registration results provide accuracies which fulfill the forestry requirements.

scholarly journals Determination of Building Model Key Points Using Multidirectional Shaded Relief Images Generated from Airborne LiDAR Data

2019 ◽  
Vol 2019 ◽  
pp. 1-19 ◽  
Author(s):  
Dong-Cheon Lee ◽  
David H. Lee ◽  
Dae Geon Lee
Keyword(s):  
Light Source ◽  
Laser Scanner ◽  
Point Clouds ◽  
Shape From Shading ◽  
Scale Space ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Surface Patches ◽  
Key Points ◽  
Shaded Relief

Light detection and ranging (LiDAR) data collected from airborne laser scanner system is one of the major sources to reconstruct Earth’s surface features. This paper presents a method for detecting model key points (MKPs) of the buildings using LiDAR point clouds. The proposed approach utilizes shaded relief images (SRIs) derived from the LiDAR data. The SRIs based on the concept of the shape from shading could provide unique information about individual surface patches of the building roofs. The main advantage of the proposed approach is to detect directly MKPs, which are primitives for 3D building modeling, without segmenting point clouds. Depending on the location of the light source, the SRIs are created differently. Therefore, integration of the multidirectional SRIs created from different locations of the light source could provide more reliable results. In addition, the vertical exaggeration (i.e., scaling Z-coordinates) is also beneficial because constituent surface patches of the roofs in the SRIs created with vertically exaggerated LiDAR data are more distinguishable. To determine the MKPs of the roofs, building data was separated from other objects using modified marker-controlled watershed algorithm in accordance with criteria to specify buildings such as area, height, and standard deviation. This process could remove the unnecessary objects such as trees, vegetation, and cars. The curvature scale space (CSS) corner detector was used to determine MKP since this method is robust to geometric changes such as rotation, translation, and scale. The proposed method was applied to simulated and real LiDAR datasets with various roof types. The experimental results show that the proposed method is effective in determining MKPs of various roof types with high level of detail (LoD).

scholarly journals Analytical Determination of Geometric Parameters of the Rotary Kiln by Novel Approach of TLS Point Cloud Segmentation

2020 ◽  
Vol 10 (21) ◽  
pp. 7652
Author(s):  
Ľudovít Kovanič ◽  
Peter Blistan ◽  
Rudolf Urban ◽  
Martin Štroner ◽  
Katarína Pukanská ◽  
...  
Keyword(s):  
Point Cloud ◽  
Laser Scanner ◽  
Point Clouds ◽  
Longitudinal Axis ◽  
Geometric Parameters ◽  
Analytical Determination ◽  
Deformation Analysis ◽  
Novel Approach ◽  
Base Method ◽  
Spatial Parameters

This research focused on determining a rotary kiln’s geometric parameters in a non-traditional geodetic way—by deriving them from a survey realized by a terrestrial laser scanner (TLS). The point cloud obtained by TLS measurement was processed to derive the longitudinal axis of the RK. Subsequently, the carrier tires’ geometric parameters and shell of the RK during the shutdown were derived. Manual point cloud selection (segmentation) is the base method for removing unnecessary points. This method is slow but precise and controllable. The proposed analytical solution is based on calculating the distance from each point to the RK’s nominal axis (local radius). Iteration using a histogram function was repeatedly applied to detect points with the same or similar radiuses. The most numerous intervals of points were selected and stored in separate files. In the comparison, we present the conformity of analytically and manually obtained files and derived geometric values of the RK-radiuses’ spatial parameters and coordinates of the carrier tires’ centers. The horizontal (X and Y directions) and vertical (Z-direction) of root–mean–square deviation (RMSD) values are up to 2 mm. RMSD of the fitting of cylinders is also up to 2 mm. The center of the carrier tires defines the longitudinal axis of the RK. Analytical segmentation of the points was repeated on the remaining point cloud for the selection of the points on the outer shell of the RK. Deformation analysis of the shell of the RK was performed using a cylinder with a nominal radius. Manually and analytically processed point clouds were investigated and mutually compared. The calculated RMSD value is up to 2 mm. Parallel cuts situated perpendicularly to the axis of the RK were created. Analysis of ovality (flattening) of the shell was performed. Additionally, we also present the effect of gradually decreasing density (number) of points on the carrier tires for their center derivation.

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