Comparison of Camera and Laser Scanner based 3D Point Cloud

Purpose This study aims to develop an optimized 3D laser point reconstruction using Descent Gradient algorithm. Precise and accurate reconstruction of 3D laser point cloud of the complex environment/object is a key solution for many industries such as construction, gaming, automobiles, aerial navigation, architecture and automation. A 2D laser scanner along with a servo motor/pan tilt/inertial measurement unit is used for generating 3D point cloud (either environment/object or both) by acquiring the real-time data from sensors. However, while generating the 3D laser point cloud, various problems related to time synchronization problem between laser and servomotor and torque variation in servomotors arise, which causes misalignment in stacking the 2D laser scan for generating the 3D point cloud of the environment. Because of the misalignment in stacking, the 2D laser scan corresponding to the erroneous angular and position information by the servomotor and the 3D laser point cloud become distorted in terms of inconsistency for measuring the dimension of the objects. Design/methodology/approach This paper addresses a modified 3D laser system assembled from a 2D laser scanner coupled with a servomotor (dynamixel motor) for developing an efficient 3D laser point cloud with the implementation of an optimization technique: descent gradient filter (DGT). The proposed approach reduces the cost function (error) in the angular and position coordinates of the servo motor caused because of torque variation and time synchronization, which resulted in enhancing the accuracy in 3D point cloud mapping for the accurate measurement of the object’s dimensions. Findings Various real-world experiments are performed with the proposed DGT filter linked with laser scanner and servomotor and an improvement of 6.5 per cent in measuring the accurate dimension of object is obtained while comparing with conventional approaches for generating a 3D laser point cloud. Originality/value This proposed technique may be applicable for various industrial applications that are based on robotics arms (such as painting, welding and cutting) in the automobile industry, the optimized measurement of object, efficient mobile robot navigation, precise 3D reconstruction of environment/object in construction, architecture applications, airborne applications and aerial navigation.

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HIGH ACCURATE POINTWISE (GEO-)REFERENCING OF A K-TLS BASED MULTI-SENSOR-SYSTEM

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-iv-4-81-2018 ◽

2018 ◽

Vol IV-4 ◽

pp. 81-88 ◽

Cited By ~ 4

Author(s):

J. Hartmann ◽

P. Trusheim ◽

H. Alkhatib ◽

J.-A. Paffenholz ◽

D. Diener ◽

...

Keyword(s):

Kalman Filter ◽

Point Cloud ◽

Laser Scanning ◽

Laser Scanner ◽

High Accuracy ◽

Laser Tracker ◽

3D Point Cloud ◽

Filter Model ◽

Measurement Frequency ◽

Set Up

Abstract. In recent years, the requirements in the industrial production, e.g., ships or planes, have been increased. In addition to high accuracy requirements with a standard deviation of 1mm, an efficient 3D object capturing is required. In terms of efficiency, kinematic laser scanning (k-TLS) has been proven its worth in recent years. It can be seen as an alternative to the well established static terrestrial laser scanning (s-TLS). However, current k-TLS based multi-sensor-systems (MSS) are not able to fulfil the high accuracy requirements. Thus, a new k-TLS based MSS and suitable processing algorithms have to be developed. In this contribution a new k-TLS based MSS will be presented. The main focus will lie on the (geo-)referencing process. Due to the high accuracy requirements, a novel procedure of external (geo-)referencing is used here. Hereby, a mobile platform, which is equipped with a profile laser scanner, will be tracked by a laser tracker. Due to the fact that the measurement frequency of the laser scanner is significantly higher than the measurement frequency of the laser tracker a direct point wise (geo-)referencing is not possible. To enable this a Kalman filter model is set up and implemented. In the prediction step each point is shifted according to the determined velocity of the platform. Because of the nonlinear motion of the platform an iterative extended Kalman filter (iEKF) is used here. Furthermore, test measurements of a panel with the k-TLS based MSS and with s-TLS were carried out. To compare the results, the 3D distances with the M3C2-algorithm between the s-TLS 3D point cloud and the k-TLS 3D point cloud are estimated. It can be noted, that the usage of a system model for the (geo-)referencing is essential. The results show that the mentioned high accuracy requirements have been achieved.

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Co-Segmentation and Superpixel-Based Graph Cuts for Building Change Detection from Bi-Temporal Digital Surface Models and Aerial Images

Remote Sensing ◽

10.3390/rs11060729 ◽

2019 ◽

Vol 11 (6) ◽

pp. 729 ◽

Cited By ~ 1

Author(s):

Shiyan Pang ◽

Xiangyun Hu ◽

Mi Zhang ◽

Zhongliang Cai ◽

Fengzhu Liu

Keyword(s):

Change Detection ◽

Point Cloud ◽

Laser Scanner ◽

Graph Cuts ◽

Aerial Images ◽

Processing Unit ◽

3D Point Cloud ◽

Point Cloud Data ◽

Cloud Data ◽

Surface Models

Thanks to the recent development of laser scanner hardware and the technology of dense image matching (DIM), the acquisition of three-dimensional (3D) point cloud data has become increasingly convenient. However, how to effectively combine 3D point cloud data and images to realize accurate building change detection is still a hotspot in the field of photogrammetry and remote sensing. Therefore, with the bi-temporal aerial images and point cloud data obtained by airborne laser scanner (ALS) or DIM as the data source, a novel building change detection method combining co-segmentation and superpixel-based graph cuts is proposed in this paper. In this method, the bi-temporal point cloud data are firstly combined to achieve a co-segmentation to obtain bi-temporal superpixels with the simple linear iterative clustering (SLIC) algorithm. Secondly, for each period of aerial images, semantic segmentation based on a deep convolutional neural network is used to extract building areas, and this is the basis for subsequent superpixel feature extraction. Again, with the bi-temporal superpixel as the processing unit, a graph-cuts-based building change detection algorithm is proposed to extract the changed buildings. In this step, the building change detection problem is modeled as two binary classifications, and acquisition of each period’s changed buildings is a binary classification, in which the changed building is regarded as foreground and the other area as background. Then, the graph cuts algorithm is used to obtain the optimal solution. Next, by combining the bi-temporal changed buildings and digital surface models (DSMs), these changed buildings are further classified as “newly built,” “taller,” “demolished”, and “lower”. Finally, two typical datasets composed of bi-temporal aerial images and point cloud data obtained by ALS or DIM are used to validate the proposed method, and the experiments demonstrate the effectiveness and generality of the proposed algorithm.

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Generating a 3D Point Cloud of a Small Steel Bridge Model Structure Using a Hokuyo UTM 30LX Laser Scanner

Lecture Notes in Civil Engineering - ICSCEA 2019 ◽

10.1007/978-981-15-5144-4_70 ◽

2020 ◽

pp. 729-735

Author(s):

Ngoc Thi Huynh ◽

Anh Thu Thi Phan

Keyword(s):

Point Cloud ◽

Laser Scanner ◽

Model Structure ◽

Steel Bridge ◽

3D Point Cloud ◽

Bridge Model ◽

Small Steel

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Towards Efficient Implementation of an Octree for a Large 3D Point Cloud

Sensors ◽

10.3390/s18124398 ◽

2018 ◽

Vol 18 (12) ◽

pp. 4398 ◽

Cited By ~ 5

Author(s):

Soohee Han

Keyword(s):

Point Cloud ◽

Laser Scanner ◽

Point Clouds ◽

Main Memory ◽

3D Point Cloud ◽

Airborne Laser Scanner ◽

Memory Efficiency ◽

3D Point Clouds ◽

Short Tunnel ◽

Better Than

The present study introduces an efficient algorithm to construct a file-based octree for a large 3D point cloud. However, the algorithm was very slow compared with a memory-based approach, and got even worse when using a 3D point cloud scanned in longish objects like tunnels and corridors. The defects were addressed by implementing a semi-isometric octree group. The approach implements several semi-isometric octrees in a group, which tightly covers the 3D point cloud, though each octree along with its leaf node still maintains an isometric shape. The proposed approach was tested using three 3D point clouds captured in a long tunnel and a short tunnel by a terrestrial laser scanner, and in an urban area by an airborne laser scanner. The experimental results showed that the performance of the semi-isometric approach was not worse than a memory-based approach, and quite a lot better than a file-based one. Thus, it was proven that the proposed semi-isometric approach achieves a good balance between query performance and memory efficiency. In conclusion, if given enough main memory and using a moderately sized 3D point cloud, a memory-based approach is preferable. When the 3D point cloud is larger than the main memory, a file-based approach seems to be the inevitable choice, however, the semi-isometric approach is the better option.

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3D Point Cloud Surface Reconstruction Based on Divide-and-Conquer Method in Laser Scanner

Journal of Physics Conference Series ◽

10.1088/1742-6596/1544/1/012118 ◽

2020 ◽

Vol 1544 ◽

pp. 012118

Author(s):

Yuan-Zhi Lyu ◽

Min Guo ◽

Ou Sha ◽

Hong-Yu Zhang

Keyword(s):

Surface Reconstruction ◽

Point Cloud ◽

Laser Scanner ◽

Divide And Conquer ◽

3D Point Cloud

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3D MODELING FOR ROCK ART DOCUMENTATION USING LIGHTWEIGHT MULTISPECTRAL CAMERA

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

10.5194/isprs-archives-xlii-2-w9-787-2019 ◽

2019 ◽

Vol XLII-2/W9 ◽

pp. 787-793 ◽

Cited By ~ 2

Author(s):

K. Zainuddin ◽

Z. Majid ◽

M. F. M. Ariff ◽

K. M. Idris ◽

M. A. Abbas ◽

...

Keyword(s):

Point Cloud ◽

3D Model ◽

Rock Art ◽

Three Dimensional ◽

Laser Scanner ◽

3D Point Cloud ◽

Short Period ◽

Dense Point ◽

Close Range ◽

Multispectral Camera

Abstract. 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.

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3D LASER SCANNING FOR PRESERVATION AND STRUCTURAL MONITORING OF HISTORIC CALIFORNIA ADOBE MISSIONS

Journal of Green Building ◽

10.3992/jgb.11.4.1.1 ◽

2016 ◽

Vol 11 (4) ◽

pp. 1-14 ◽

Cited By ~ 1

Author(s):

H. M. Böttger ◽

C. J. Arce Bazán ◽

N. P. Saarman

Keyword(s):

Native Americans ◽

San Francisco ◽

Point Cloud ◽

Laser Scanning ◽

Laser Scanner ◽

Monitoring Program ◽

Lessons Learned ◽

Structural Monitoring ◽

Special Focus ◽

3D Point Cloud

INTRODUCTION At the University of San Francisco Architecture & Community Design Program, the Architectural Engineering curriculum utilizes a Leica ScanStation C10 3D Laser Scanner to document historic structures and monitor their structural behavior. Some of the oldest structures in the State of California are the historic adobe missions built by Native Americans and Spanish Catholic missionaries between 1769 and 1833. California is a region of very high seismic activity, and the adobe structures have withstood significant earthquakes and other erosive or destructive forces over their lifetime. However, they are sensitive structures in need of active preservation and very few original adobe buildings remain. Working together with local structural engineers who specialize in seismic restoration of historic adobe structures, USF students have conducted laser scanning at Mission Santa Cruz and Mission San Miguel Arcángel, creating extensive 3D point cloud records, and developing architectural drawings which establish the current state of these structures for the purposes of historic preservation and structural study. Because of the delicate and irregular nature of these structures, the 3D laser scanner is the most appropriate tool for detailed yet non-invasive documentation. Completed in 1821, Mission San Miguel Arcángel suffered significant damage in the nearby 2003 San Simeon earthquake. The original adobe structure has undergone partial repairs such as banding at the top of the walls of the Sacristy. Using the 3D laser scanner, thorough scans are stitched together to create full interior and exterior 3D point cloud files, which are processed in Leica Cyclone and Autodesk Recap, and then imported into AutoCAD to create detailed line drawings of plans, elevations and sections of significant areas. Wall lean and other indicators of crack progress and deterioration are areas of special focus. With these records, a structural monitoring program has begun to document the condition of the buildings in wet seasons and dry seasons, and to determine the long-term effect of seismic restorations which have been implemented. This paper presents a detailed account of the process, pedagogical value and structural and architectural lessons learned over the course of the 3D scanning of these valuable heritage landmarks.

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