Hydrographical survey using point cloud data from laser scanner and echo sounder

2016 ◽  
Author(s):  
Pradya Prempraneerach ◽  
Manusak Janthong ◽  
Kraisak Phothongkum ◽  
Channarong Choosui ◽  
Surasak Timpitak
Keyword(s):  
Point Cloud ◽  
Laser Scanner ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Echo Sounder

scholarly journals On-Site 4-in-1 Alignment: Visualization and Interactive CAD Model Retrofitting Using UAV, LiDAR’s Point Cloud Data, and Video

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3908 ◽  
Author(s):  
Pavan Kumar B. N. ◽  
Ashok Kumar Patil ◽  
Chethana B. ◽  
Young Ho Chai
Keyword(s):  
Computer Aided Design ◽  
Point Cloud ◽  
Laser Scanner ◽  
Video Frame ◽  
Cad Model ◽  
Point Cloud Data ◽  
Registration Method ◽  
Industrial Facilities ◽  
Cloud Data ◽  
Generic Framework

Acquisition of 3D point cloud data (PCD) using a laser scanner and aligning it with a video frame is a new approach that is efficient for retrofitting comprehensive objects in heavy pipeline industrial facilities. This work contributes a generic framework for interactive retrofitting in a virtual environment and an unmanned aerial vehicle (UAV)-based sensory setup design to acquire PCD. The framework adopts a 4-in-1 alignment using a point cloud registration algorithm for a pre-processed PCD alignment with the partial PCD, and frame-by-frame registration method for video alignment. This work also proposes a virtual interactive retrofitting framework that uses pre-defined 3D computer-aided design models (CAD) with a customized graphical user interface (GUI) and visualization of a 4-in-1 aligned video scene from a UAV camera in a desktop environment. Trials were carried out using the proposed framework in a real environment at a water treatment facility. A qualitative and quantitative study was conducted to evaluate the performance of the proposed generic framework from participants by adopting the appropriate questionnaire and retrofitting task-oriented experiment. Overall, it was found that the proposed framework could be a solution for interactive 3D CAD model retrofitting on a combination of UAV sensory setup-acquired PCD and real-time video from the camera in heavy industrial facilities.

Research on Stereo Image Acquisition Technology of 3D Printing

2014 ◽  
Vol 644-650 ◽  
pp. 2656-2660
Author(s):  
Yao Cheng ◽  
Guang Xue Chen ◽  
Chen Chen ◽  
Jiang Ping Yuan
Keyword(s):  
3D Printing ◽  
Point Cloud ◽  
Image Acquisition ◽  
Laser Scanner ◽  
Stereo Image ◽  
Object Model ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Engineering Software ◽  
Hand Model

In the process of 3D printing, stereo image acquisition is the basis and premise of 3D modeling so that it’s important to study the acquisition methods and techniques. This paper will study the process of point cloud data acquisition of a hand model by using handheld laser scanner REVscan, and processed by the reverse engineering software Geomagic Studio. Using the object model captured, we can greatly improve the efficiency and accuracy, as well as reduce the cycle of the 3D printing. This will help achieve the transmission of 3D printing data without geographical restrictions, in which truly realize the concept "What You See Is What You Get".

Design of Light-Small Mobile 3D Laser Measurement System

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.

scholarly journals DEVELOPMENT OF TECHNIQUE FOR SELECTING POINT CLOUD DATA WITH HIGH PRECISION IN MULTIPOINT MEASUREMENT WITH LASER SCANNER

2016 ◽  
Vol 72 (2) ◽  
pp. I_209-I_218
Author(s):  
Jun SAKURAI ◽  
Shigenori TANAKA ◽  
Kenji NAKAMURA ◽  
Ryuichi IMAI ◽  
Satoshi KUBOTA ◽  
...  
Keyword(s):  
High Precision ◽  
Point Cloud ◽  
Laser Scanner ◽  
Point Cloud Data ◽  
Cloud Data

Research on Earthwork Calculating Methods Based on 3D Laser Scanning Technology

2012 ◽  
Vol 204-208 ◽  
pp. 618-621
Author(s):  
Bao Xing Zhou ◽  
Jian Ping Yue ◽  
Jin Li
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Accuracy Evaluation ◽  
Point Cloud Data ◽  
3D Laser Scanning ◽  
Cloud Data ◽  
Calculating Method ◽  
Validation Experiment ◽  
High Resolution Reconstruction

Terrestrial laser scanner (TLS) can provide the measurement of a large number of physical points distributed on the observed surface. A fast earthwork calculating method is proposed based on the redundant number of acquired points, which leads to a very accurate and high resolution reconstruction of the observed surfaces. This paper describes the three main steps of the method, namely the acquisition of the earthwork data based on TLS, the pre-processing of point cloud data, the earthwork calculation and accuracy evaluation based on point cloud data. Furthermore, it illustrates the performance of the proposed method with a validation experiment.

scholarly journals Hybrid approach for alignment of a pre-processed three-dimensional point cloud, video, and CAD model using partial point cloud in retrofitting applications

2018 ◽  
Vol 14 (3) ◽  
pp. 155014771876645 ◽  
Author(s):  
Ashok Kumar Patil ◽  
G Ajay Kumar ◽  
Tae-Hyoung Kim ◽  
Young Ho Chai
Keyword(s):  
Computer Aided Design ◽  
Point Cloud ◽  
Hybrid Approach ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Video Scene ◽  
Engineering Models ◽  
Aided Design

Acquiring the three-dimensional point cloud data of a scene using a laser scanner and the alignment of the point cloud data within a real-time video environment view of a camera is a very new concept and is an efficient method for constructing, monitoring, and retrofitting complex engineering models in heavy industrial plants. This article presents a novel prototype framework for virtual retrofitting applications. The workflow includes an efficient 4-in-1 alignment, beginning with the coordination of pre-processed three-dimensional point cloud data using a partial point cloud from LiDAR and alignment of the pre-processed point cloud within the video scene using a frame-by-frame registering method. Finally, the proposed approach can be utilized in pre-retrofitting applications by pre-generated three-dimensional computer-aided design models virtually retrofitted with the help of a synchronized point cloud, and a video scene is efficiently visualized using a wearable virtual reality device. The prototype method is demonstrated in a real-world setting, using the partial point cloud from LiDAR, pre-processed point cloud data, and video from a two-dimensional camera.

scholarly journals A NOVEL TIE POINT BASED STRATEGY FOR POINT CLOUD AND IMAGERY DATA FINE REGISTRATION

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 331-334
Author(s):  
M. Eslami ◽  
M. Saadatseresht
Keyword(s):  
Point Cloud ◽  
Laser Scanner ◽  
Normal Vector ◽  
Point Cloud Data ◽  
Object Space ◽  
Cloud Data ◽  
Conditional Equation ◽  
Novel Strategy ◽  
Orientation Parameters ◽  
Fine Registration

Abstract. Laser scanner generated point cloud and photogrammetric imagery are complimentary data for many applications and services. Misalignment between imagery and point cloud data is a common problem, which causes to inaccurate products and procedures. In this paper, a novel strategy is proposed for coarse to fine registration between close-range imagery and terrestrial laser scanner point cloud data. In such a case, tie points are extracted and matched from photogrammetric imagery and preprocessing is applied on generated tie points to eliminate non-robust ones. At that time, for every tie point, two neighbor pixels are selected and matched in all overlapped images. After that, coarse interior orientation parameters (IOPs) and exterior orientation parameters (EOPs) of the images are employed to reconstruct object space points of the tie point and its two neighbor pixels. Then, corresponding nearest points to the object space photogrammetric points are estimated in the point cloud data. Estimated three point cloud points are used to calculate a plane and its normal vector. Theoretically, every object space tie point should be located on the aforementioned plane, which is used as conditional equation alongside the collinearity equation to fine register the photogrammetric imagery network. Attained root mean square error (RMSE) results on check points, have been shown less than 2.3 pixels, which shows the accuracy, completeness and robustness of the proposed method.

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