ANALYSIS OF THE POSSIBILITIES OF USING LOW-COST SCANNING SYSTEM IN 3D MODELING

The laser scanning technique is still a very popular and fast growing method of obtaining information on modeling 3D objects. The use of low-cost miniature scanners creates new opportunities for small objects of 3D modeling based on point clouds acquired from the scan. The same, the development of accuracy and methods of automatic processing of this data type is noticeable. The article presents methods of collecting raw datasets in the form of a point-cloud using a low-cost ground-based laser scanner FabScan. As part of the research work 3D scanner from an open source FabLab project was constructed. In addition, the results for the analysis of the geometry of the point clouds obtained by using a low-cost laser scanner were presented. Also, some analysis of collecting data of different structures (made of various materials such as: glass, wood, paper, gum, plastic, plaster, ceramics, stoneware clay etc. and of different shapes: oval and similar to oval and prism shaped) have been done. The article presents two methods used for analysis: the first one - visual (general comparison between the 3D model and the real object) and the second one - comparative method (comparison between measurements on models and scanned objects using the mean error of a single sample of observations). The analysis showed, that the low-budget ground-based laser scanner FabScan has difficulties with collecting data of non-oval objects. Items built of glass painted black also caused problems for the scanner. In addition, the more details scanned object contains, the lower the accuracy of the collected point-cloud is. Nevertheless, the accuracy of collected data (using oval-straight shaped objects) is satisfactory. The accuracy, in this case, fluctuates between ± 0,4 mm and ± 1,0 mm whereas when using more detailed objects or a rectangular shaped prism the accuracy is much more lower, between 2,9 mm and ± 9,0 mm. Finally, the publication presents the possibility (for the future expansion of research) of modernization FabScan by the implementation of a larger amount of camera-laser units. This will enable spots the registration , that are less visible.

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ANALYSIS OF THE POSSIBILITIES OF USING LOW-COST SCANNING SYSTEM IN 3D MODELING

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xli-b3-261-2016 ◽

2016 ◽

Vol XLI-B3 ◽

pp. 261-267

Author(s):

M. Kedzierski ◽

D. Wierzbickia ◽

A. Fryskowska ◽

B. Chlebowska

Keyword(s):

3D Modeling ◽

Point Cloud ◽

Laser Scanning ◽

Low Cost ◽

Comparative Method ◽

Research Work ◽

Laser Scanner ◽

Method Comparison ◽

Point Clouds ◽

Scanning System

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Development, Calibration and Evaluation of a Portable and Direct Georeferenced Laser Scanning System for Kinematic 3D Mapping

Journal of Applied Geodesy ◽

10.1515/jag-2015-0011 ◽

2015 ◽

Vol 9 (4) ◽

Cited By ~ 4

Author(s):

Erik Heinz ◽

Christian Eling ◽

Markus Wieland ◽

Lasse Klingbeil ◽

Heiner Kuhlmann

Keyword(s):

Laser Scanning ◽

Attitude Determination ◽

Low Cost ◽

Laser Scanner ◽

Point Clouds ◽

Scanning System ◽

Planar Surfaces ◽

Laser Scanners ◽

Scanning Geometry ◽

Laser Scanning System

AbstractIn recent years, kinematic laser scanning has become increasingly popular because it offers many benefits compared to static laser scanning. The advantages include both saving of time in the georeferencing and a more favorable scanning geometry. Often mobile laser scanning systems are installed on wheeled platforms, which may not reach all parts of the object. Hence, there is an interest in the development of portable systems, which remain operational even in inaccessible areas. The development of such a portable laser scanning system is presented in this paper. It consists of a lightweight direct georeferencing unit for the position and attitude determination and a small low-cost 2D laser scanner. This setup provides advantages over existing portable systems that employ heavy and expensive 3D laser scanners in a profiling mode.A special emphasis is placed on the system calibration, i. e. the determination of the transformation between the coordinate frames of the direct georeferencing unit and the 2D laser scanner. To this end, a calibration field is used, which consists of differently orientated georeferenced planar surfaces, leading to estimates for the lever arms and boresight angles with an accuracy of mm and one-tenth of a degree. Finally, point clouds of the mobile laser scanning system are compared with georeferenced point clouds of a high-precision 3D laser scanner. Accordingly, the accuracy of the system is in the order of cm to dm. This is in good agreement with the expected accuracy, which has been derived from the error propagation of previously estimated variance components.

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

Remote Sensing ◽

10.3390/rs10111754 ◽

2018 ◽

Vol 10 (11) ◽

pp. 1754 ◽

Cited By ~ 5

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.

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LOW-COST WHEELED ROBOT-BORNE LASER SCANNING SYSTEM FOR INDOOR AND OUTDOOR 3D MAPPING APPLICATION

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-2-w13-1155-2019 ◽

2019 ◽

Vol XLII-2/W13 ◽

pp. 1155-1159

Author(s):

W. Wu ◽

C. Chen ◽

Y. Cong ◽

Z. Dong ◽

J. Li ◽

...

Keyword(s):

Laser Scanning ◽

Low Cost ◽

Laser Scanner ◽

Point Clouds ◽

Measurement Unit ◽

Scanning System ◽

Outdoor Scenes ◽

Wheeled Robot ◽

Laser Scanning System ◽

Indoor And Outdoor

Abstract. Aiming to accomplish automatic and real-time three-dimensional mapping in both indoor and outdoor scenes, a low-cost wheeled robot-borne laser scanning system is proposed in this paper. The system includes a laser scanner, an inertial measurement unit, a modified turtlebot3 two-wheel differential chassis and etc. To achieve a globally consistent map, the system performs global trajectory optimization after detecting the loop closure. Experiments are undertaken in two typical indoor/outdoor scenes that is an underground car park and a road environment in the campus of Wuhan University. The point clouds acquired by the proposed system are quantitatively evaluated by comparing the derived point clouds with the ground truth data collected by a RIEGL VZ 400 laser scanner. The results present an accuracy of 90% points below 0.1 meter error in the tested scene, showing that its applicability and potential in indoor and mapping applications.

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Design of Light-Small Mobile 3D Laser Measurement System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.405-408.3032 ◽

2013 ◽

Vol 405-408 ◽

pp. 3032-3036

Author(s):

Yi Bo Sun ◽

Xin Qi Zheng ◽

Zong Ren Jia ◽

Gang Ai

Keyword(s):

Point Cloud ◽

Laser Scanning ◽

Laser Scanner ◽

Digital Camera ◽

Scanning System ◽

Point Cloud Data ◽

3D Laser Scanning ◽

Large Area ◽

Cloud Data ◽

Laser Scanning System

At present, most of the commercial 3D laser scanning measurement systems do work for a large area and a big scene, but few shows their advantage in the small area or small scene. In order to solve this shortage, we design a light-small mobile 3D laser scanning system, which integrates GPS, INS, laser scanner and digital camera and other sensors, to generate the Point Cloud data of the target through data filtering and fusion. This system can be mounted on airborne or terrestrial small mobile platform and enables to achieve the goal of getting Point Cloud data rapidly and reconstructing the real 3D model. Compared to the existing mobile 3D laser scanning system, the system we designed has high precision but lower cost, smaller hardware and more flexible.

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Influence of ULS data acquisition characteristics on the achievable stem reconstruction accuracies

10.5194/egusphere-egu2020-7378 ◽

2020 ◽

Author(s):

Moritz Bruggisser ◽

Johannes Otepka ◽

Norbert Pfeifer ◽

Markus Hollaus

Keyword(s):

Point Cloud ◽

Laser Scanning ◽

Laser Scanner ◽

Point Clouds ◽

Stem Diameter ◽

Forest Monitoring ◽

Individual Tree ◽

Detection Rates ◽

Point Count ◽

Tree Stem

Unmanned aerial vehicles-borne laser scanning (ULS) allows time-efficient acquisition of high-resolution point clouds on regional extents at moderate costs. The quality of ULS-point clouds facilitates the 3D modelling of individual tree stems, what opens new possibilities in the context of forest monitoring and management. In our study, we developed and tested an algorithm which allows for i) the autonomous detection of potential stem locations within the point clouds, ii) the estimation of the diameter at breast height (DBH) and iii) the reconstruction of the tree stem. In our experiments on point clouds from both, a RIEGL miniVUX-1DL and a VUX-1UAV, respectively, we could detect 91.0 % and 77.6 % of the stems within our study area automatically. The DBH could be modelled with biases of 3.1 cm and 1.1 cm, respectively, from the two point cloud sets with respective detection rates of 80.6 % and 61.2 % of the trees present in the field inventory. The lowest 12 m of the tree stem could be reconstructed with absolute stem diameter differences below 5 cm and 2 cm, respectively, compared to stem diameters from a point cloud from terrestrial laser scanning. The accuracy of larger tree stems thereby was higher in general than the accuracy for smaller trees. Furthermore, we recognized a small influence only of the completeness with which a stem is covered with points, as long as half of the stem circumference was captured. Likewise, the absolute point count did not impact the accuracy, but, in contrast, was critical to the completeness with which a scene could be reconstructed. The precision of the laser scanner, on the other hand, was a key factor for the accuracy of the stem diameter estimation.&#160; The findings of this study are highly relevant for the flight planning and the sensor selection of future ULS acquisition missions in the context of forest inventories.

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Accurate Calibration of a Self-Developed Vehicle-Borne LiDAR Scanning System

Journal of Sensors ◽

10.1155/2021/8816063 ◽

2021 ◽

Vol 2021 ◽

pp. 1-18

Author(s):

Ming Guo ◽

Bingnan Yan ◽

Tengfei Zhou ◽

Deng Pan ◽

Guoli Wang

Keyword(s):

Point Cloud ◽

Laser Scanner ◽

Measurement Data ◽

Point Clouds ◽

Calibration Method ◽

Linear Interpolation ◽

Measurement Unit ◽

Scanning System ◽

High Precision Measurement ◽

Distance Ratio

To obtain high-precision measurement data using vehicle-borne light detection and ranging (LiDAR) scanning (VLS) systems, calibration is necessary before a data acquisition mission. Thus, a novel calibration method based on a homemade target ball is proposed to estimate the system mounting parameters, which refer to the rotational and translational offsets between the LiDAR sensor and inertial measurement unit (IMU) orientation and position. Firstly, the spherical point cloud is fitted into a sphere to extract the coordinates of the centre, and each scan line on the sphere is fitted into a section of the sphere to calculate the distance ratio from the centre to the nearest two sections, and the attitude and trajectory parameters of the centre are calculated by linear interpolation. Then, the real coordinates of the centre of the sphere are calculated by measuring the coordinates of the reflector directly above the target ball with the total station. Finally, three rotation parameters and three translation parameters are calculated by two least-squares adjustments. Comparisons of the point cloud before and after calibration and the calibrated point clouds with the point cloud obtained by the terrestrial laser scanner show that the accuracy significantly improved after calibration. The experiment indicates that the calibration method based on the homemade target ball can effectively improve the accuracy of the point cloud, which can promote VLS development and applications.

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POTENTIAL OF FULL WAVEFORM AIRBORNE LASER SCANNING DATA FOR URBAN AREA CLASSIFICATION – TRANSFER OF CLASSIFICATION APPROACHES BETWEEN MISSIONS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xl-7-w3-1317-2015 ◽

2015 ◽

Vol XL-7/W3 ◽

pp. 1317-1323 ◽

Cited By ~ 3

Author(s):

G. Tran ◽

D. Nguyen ◽

M. Milenkovic ◽

N. Pfeifer

Keyword(s):

Point Cloud ◽

Laser Scanning ◽

Laser Scanner ◽

Point Clouds ◽

Surface Model ◽

Knowledge Based ◽

Full Waveform ◽

Airborne Laser ◽

Point Density ◽

Area Classification

Full-waveform (FWF) LiDAR (Light Detection and Ranging) systems have their advantage in recording the entire backscattered signal of each emitted laser pulse compared to conventional airborne discrete-return laser scanner systems. The FWF systems can provide point clouds which contain extra attributes like amplitude and echo width, etc. In this study, a FWF data collected in 2010 for Eisenstadt, a city in the eastern part of Austria was used to classify four main classes: buildings, trees, waterbody and ground by employing a decision tree. Point density, echo ratio, echo width, normalised digital surface model and point cloud roughness are the main inputs for classification. The accuracy of the final results, correctness and completeness measures, were assessed by comparison of the classified output to a knowledge-based labelling of the points. Completeness and correctness between 90% and 97% was reached, depending on the class. While such results and methods were presented before, we are investigating additionally the transferability of the classification method (features, thresholds …) to another urban FWF lidar point cloud. Our conclusions are that from the features used, only echo width requires new thresholds. A data-driven adaptation of thresholds is suggested.

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INDOOR MAPPING OF A COMPLEX CULTURAL HERITAGE SCENE USING TLS AND HMLS LASER SCANNING

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xliii-b2-2021-605-2021 ◽

2021 ◽

Vol XLIII-B2-2021 ◽

pp. 605-612

Author(s):

V. E. Oniga ◽

A. I. Breaban ◽

E. I. Alexe ◽

C. Văsii

Keyword(s):

Standard Deviation ◽

Cultural Heritage ◽

Long Range ◽

Interior Design ◽

Point Cloud ◽

Laser Scanning ◽

Laser Scanner ◽

Point Clouds ◽

Acquisition Time ◽

Wide Range

Abstract. Indoor mapping and modelling is an important research subject with application in a wide range of domains including interior design, real estate, cultural heritage conservation and restoration. There are multiple sensors applicable for 3D indoor modelling, but the laser scanning technique is frequently used because of the acquisition time, detailed information and accuracy. In this paper, the efficiency of the Maptek I-Site 8820 terrestrial scanner, which is a long-range laser scanner and the accuracy of a HMLS point cloud acquired with a mobile scanner, namely GeoSlam Zeb Horizon were tested for indoor mapping. Aula Magna “Carmen Silva” of the “Gheorghe Asachi” Technical University of Iasi is studied in the current paper since the auditorium interior creates a distinct environment that combines complex geometric structures with architectural lighting and for preserving its great cultural value, the monument has a national historical significance. The registration process of the TLS point clouds was done using two methods: a semi-automatic one with artificial targets and a completely automatic one, based on Iterative Closest Point (ICP) algorithm. The resulted TLS point cloud was analysed in relation to the HMLS point cloud by computing the M3C2 (Multiscale Model to Model Cloud Comparison), obtaining a standard deviation of 2.1 cm and by investigating the Hausdorff distances from which resulted a standard deviation (σ) of 1.6 cm. Cross-sections have been extracted from the HMLS and TLS point clouds and after comparing the sections, 80% of the sigma values are less or equal to 1 cm. The results show high potential of using HMLS and also a long-range laser scanner for 3D modelling of complex scenes, the occlusion effect in the case of TLS being only 5% of the scanned area.

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PROGRESS ON ISPRS BENCHMARK ON MULTISENSORY INDOOR MAPPING AND POSITIONING

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-2-w13-1709-2019 ◽

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

Abstract. 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.

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