scholarly journals THE USE OF MOBILE LASER SCANNING DATA AND UNMANNED AERIAL VEHICLE IMAGES FOR 3D MODEL RECONSTRUCTION

2013 ◽  
Vol XL-1/W2 ◽  
pp. 419-423 ◽  
Author(s):  
L. Zhu ◽  
A. Jaakkola ◽  
J. Hyyppä
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Laser Scanning ◽  
3D Model ◽  
Model Reconstruction ◽  
3D Model Reconstruction ◽  
Aerial Vehicle

3D Model Reconstruction Based on Laser Scanning Technique

2011 ◽  
Vol 48 (8) ◽  
pp. 081201
Author(s):  
Nguyen Tien Thanh Nguyen Tien Thanh ◽  
刘修国 Liu Xiuguo ◽  
王红平 Wang Hongping ◽  
于明旭 Yu Mingxu ◽  
周文浩 Zhou Wenhao
Keyword(s):  
Laser Scanning ◽  
3D Model ◽  
Model Reconstruction ◽  
Scanning Technique ◽  
3D Model Reconstruction

scholarly journals DATA MANAGEMENT FRAMEWORK OF DRONE-BASED 3D MODEL RECONSTRUCTION OF DISASTER SITE

2016 ◽  
Vol XLI-B4 ◽  
pp. 31-33
Author(s):  
C. Kim ◽  
H. Moon ◽  
W. Lee
Keyword(s):  
Information Acquisition ◽  
3D Model ◽  
Image Data ◽  
Model Reconstruction ◽  
Current Image ◽  
Management Framework ◽  
3D Model Reconstruction ◽  
Disaster Situation ◽  
Aerial Vehicle ◽  
Collapsed Buildings

To rescue peoples in the disaster site in time, information acquisition of current feature of collapsed buildings and terrain is quite important for disaster site rescue manager. Based on information about disaster site, they can accurately plan the rescue process and remove collapsed buildings or other facilities. However, due to the harsh condition of disaster areas, rapid and accurate acquisition of disaster site information is not an easy task. There are possibilities of further damages in the collapse and there are also difficulties in acquiring information about current disaster situation due to large disaster site and limited rescue resources. To overcome these circumstances of disaster sites, an unmanned aerial vehicle, commonly known as a drone is used to rapidly and effectively acquire current image data of the large disaster areas. Then, the procedure of drone-based 3D model reconstruction visualization function of developed system is presented.

Integration of Image and Laser Scanning Data Based on Selected Example

2014 ◽  
Vol 19 (2-3) ◽  
pp. 37-44 ◽  
Author(s):  
Sławomir Mikrut ◽  
Agnieszka Moskal ◽  
Urszula Marmol
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
3D Model ◽  
Image Data ◽  
Point Clouds ◽  
Model Reconstruction ◽  
Railway Line ◽  
3D Model Reconstruction ◽  
Conducting Research ◽  
The Village

Abstract The paper aims at presentation of results of research on integration of image and laser data based on selected example. Since a few years the authors have been conducting research on processing image data, and those obtained from laser scanning in the form of the so-called point cloud. In experiments data from terrestrial and mobile laser scanning gained for two different objects were compared: a parish house from Goźlice located in the open-air ethnographic museum at the village of Tokarnia, Poland, and part of the Cracow-Warsaw railway line. The results of those experiments proved that data in the form of point cloud were not always sufficient for a precise 3D model reconstruction. Supplementing point clouds with photogrammetric images seems to be the best solution.

scholarly journals DATA MANAGEMENT FRAMEWORK OF DRONE-BASED 3D MODEL RECONSTRUCTION OF DISASTER SITE

2016 ◽  
Vol XLI-B4 ◽  
pp. 31-33 ◽  
Author(s):  
C. Kim ◽  
H. Moon ◽  
W. Lee
Keyword(s):  
Information Acquisition ◽  
3D Model ◽  
Image Data ◽  
Model Reconstruction ◽  
Current Image ◽  
Management Framework ◽  
3D Model Reconstruction ◽  
Disaster Situation ◽  
Aerial Vehicle ◽  
Collapsed Buildings

To rescue peoples in the disaster site in time, information acquisition of current feature of collapsed buildings and terrain is quite important for disaster site rescue manager. Based on information about disaster site, they can accurately plan the rescue process and remove collapsed buildings or other facilities. However, due to the harsh condition of disaster areas, rapid and accurate acquisition of disaster site information is not an easy task. There are possibilities of further damages in the collapse and there are also difficulties in acquiring information about current disaster situation due to large disaster site and limited rescue resources. To overcome these circumstances of disaster sites, an unmanned aerial vehicle, commonly known as a drone is used to rapidly and effectively acquire current image data of the large disaster areas. Then, the procedure of drone-based 3D model reconstruction visualization function of developed system is presented.

scholarly journals THE INTEGRATED 3D SURVEY FOR UNDERGROUND ARCHAEOLOGICAL ENVIRONMENT

2019 ◽  
Vol XLII-2/W9 ◽  
pp. 311-317 ◽  
Author(s):  
D. Ebolese ◽  
M. Lo Brutto ◽  
G. Dardanelli
Keyword(s):  
Cultural Heritage ◽  
Unmanned Aerial Vehicle ◽  
Laser Scanning ◽  
3D Model ◽  
Southern Italy ◽  
Three Dimensional ◽  
Point Of View ◽  
Articulated Structures ◽  
Aerial Vehicle

<p><strong>Abstract.</strong> The task of documentation and conservation of Cultural Heritage defines the challenges that geomatics techniques have to overtake in order to provide different solutions that combine the automation of processes with accurate results. The employment of integrated technologies allows improving the documentation of Cultural Heritage from a quantitative and qualitative point of view. The use of range and image-based techniques ensures the possibility to completely record articulated structures such as building with underground environments. The latter present often problematic survey conditions that imposed well planned and appropriate solutions. In this context, the paper presents the results of a 3D survey of the underground “Sybil hypogeum” and the related overhead church located in the Archaeological Park of Lilibeo (Marsala, Southern Italy). An integrated survey was planned in order to combine laser scanning technology with terrestrial-based and Unmanned Aerial Vehicle (UAV)-based photogrammetry to acquire the three-dimensional data of the whole complex (underground environments and overhead church). The aims of the work are related to test a topographic approach by a traverse method for scans registration and to archive a complete and detailed 3D model of the whole area. This model could be used to prevent the risk of information’s loss and to improve the knowledge of the site.</p>

scholarly journals Comparison of Coniferous Plantation Heights Using Unmanned Aerial Vehicle (UAV) Laser Scanning and Stereo Photogrammetry

2021 ◽  
Vol 13 (15) ◽  
pp. 2885
Author(s):  
Mei Li ◽  
Zengyuan Li ◽  
Qingwang Liu ◽  
Erxue Chen
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Prediction Accuracy ◽  
Laser Scanning ◽  
Forest Stand ◽  
Coniferous Plantation ◽  
Point Density ◽  
Stereo Photogrammetry ◽  
Aerial Vehicle ◽  
Stand Height ◽  
Median Height

Plantation forests play a critical role in forest products and ecosystems. Unmanned aerial vehicle (UAV) remote sensing has become a promising technology in forest related applications. The stand heights will reflect the growth and competition of individual trees in plantation. UAV laser scanning (ULS) and UAV stereo photogrammetry (USP) can both be used to estimate stand heights using different algorithms. Thus, this study aimed to deeply explore the variations of four kinds of stand heights including mean height, Lorey’s height, dominated height, and median height of coniferous plantations using different models based on ULS and USP data. In addition, the impacts of thinned point density of 30 pts to 10 pts, 5 pts, 1 pts, and 0.8 pts/m2 were also analyzed. Forest stand heights were estimated from ULS and USP data metrics by linear regression and the prediction accuracy was assessed by 10-fold cross validation. The results showed that the prediction accuracy of the stand heights using metrics from USP was basically as good as that of ULS. Lorey’s height had the highest prediction accuracy, followed by dominated height, mean height, and median height. The correlation between height percentiles metrics from ULS and USP increased with the increased height. Different stand heights had their corresponding best height percentiles as variables based on stand height characteristics. Furthermore, canopy height model (CHM)-based metrics performed slightly better than normalized point cloud (NPC)-based metrics. The USP was not able to extract exact terrain information in a continuous coniferous plantation for forest canopy cover (CC) over 0.49. The combination of USP and terrain from ULS can be used to estimate forest stand heights with high accuracy. In addition, the estimation accuracy of each forest stand height was slightly affected by point density, which can also be ignored.

Sequential Depth Completion With Confidence Estimation for 3D Model Reconstruction

2021 ◽  
Vol 6 (2) ◽  
pp. 327-334
Author(s):  
Khang Truong Giang ◽  
Soohwan Song ◽  
Daekyum Kim ◽  
Sunghee Choi
Keyword(s):  
3D Model ◽  
Model Reconstruction ◽  
Confidence Estimation ◽  
3D Model Reconstruction
Sign in / Sign up

Export Citation Format

Share Document