UAV-based automatic generation of high-resolution panorama at a construction site with a focus on preprocessing for image stitching

2017 ◽  
Vol 84 ◽  
pp. 70-80 ◽  
Author(s):  
Seongdeok Bang ◽  
Hongjo Kim ◽  
Hyoungkwan Kim
Keyword(s):  
High Resolution ◽  
Automatic Generation ◽  
Image Stitching ◽  
Construction Site

scholarly journals HRTEM image-stitching for measurement of distances

2020 ◽  
Vol 5 (1) ◽  
pp. 13-17
Author(s):  
György Zoltán Radnóczi ◽  
Zoltán Herceg ◽  
Tamás Rafael Kiss
Keyword(s):  
Electron Beam ◽  
High Resolution ◽  
Single Crystal ◽  
Image Stitching ◽  
Hrtem Image ◽  
Lattice Image ◽  
High Resolution Tem ◽  
Better Than

AbstractVery accurate measurement of distances in the order of several µm is demonstrated on a single crystal Si sample by counting the lattice fringes on stitched high resolution TEM/STEM images. Stitching of TEM images commonly relies on correspondence points found in the image, however, the nearly perfect periodic nature of a lattice image renders such a procedure very unreliable. To overcome this difficulty artificial correspondence points are created on the sample using the electron beam. An accuracy better than 1% can be reached while measuring distances in the order of 1 µm. A detailed description of the process is provided, and its usability for accurately measuring large distances is discussed in detail.

scholarly journals AUTOMATIC GENERATION OF BUILDING MAPPING USING DIGITAL, VERTICAL AND AERIAL HIGH RESOLUTION PHOTOGRAPHS AND LIDAR POINT CLOUDS

2016 ◽  
Vol XLI-B7 ◽  
pp. 171-176 ◽  
Author(s):  
W. Barragán ◽  
A. Campos ◽  
G. Sanchez
Keyword(s):  
High Resolution ◽  
Point Cloud ◽  
Spectral Band ◽  
Point Clouds ◽  
Automatic Generation ◽  
Aerial Photographs ◽  
Band Combination ◽  
Segmentation Algorithms ◽  
Digital Processes ◽  
Overall Effectiveness

The objective of this research is automatic generation of buildings in the interest areas. This research was developed by using high resolution vertical aerial photographs and the LIDAR point cloud through radiometric and geometric digital processes. The research methodology usesknown building heights and various segmentation algorithms and spectral band combination. The overall effectiveness of the algorithm is 97.2% with the test data.

scholarly journals FAST PROBABILISTIC FUSION OF 3D POINT CLOUDS VIA OCCUPANCY GRIDS FOR SCENE CLASSIFICATION

2016 ◽  
Vol III-3 ◽  
pp. 325-332
Author(s):  
Andreas Kuhn ◽  
Hai Huang ◽  
Martin Drauschke ◽  
Helmut Mayer
Keyword(s):  
High Resolution ◽  
Point Cloud ◽  
State Of The Art ◽  
Point Clouds ◽  
Automatic Generation ◽  
Scene Classification ◽  
Semantic Classification ◽  
3D Point Clouds ◽  
Occupancy Grids ◽  
High Scalability

High resolution consumer cameras on Unmanned Aerial Vehicles (UAVs) allow for cheap acquisition of highly detailed images, e.g., of urban regions. Via image registration by means of Structure from Motion (SfM) and Multi View Stereo (MVS) the automatic generation of huge amounts of 3D points with a relative accuracy in the centimeter range is possible. Applications such as semantic classification have a need for accurate 3D point clouds, but do not benefit from an extremely high resolution/density. In this paper, we, therefore, propose a fast fusion of high resolution 3D point clouds based on occupancy grids. The result is used for semantic classification. In contrast to state-of-the-art classification methods, we accept a certain percentage of outliers, arguing that they can be considered in the classification process when a per point belief is determined in the fusion process. To this end, we employ an octree-based fusion which allows for the derivation of outlier probabilities. The probabilities give a belief for every 3D point, which is essential for the semantic classification to consider measurement noise. For an example point cloud with half a billion 3D points (cf. Figure 1), we show that our method can reduce runtime as well as improve classification accuracy and offers high scalability for large datasets.

scholarly journals A Super-Resolution Reconstruction Driven Helmet Detection Workflow

2022 ◽  
Vol 12 (2) ◽  
pp. 545
Author(s):  
Yicheng Liu ◽  
Zhipeng Li ◽  
Bixiong Zhan ◽  
Ju Han ◽  
Yan Liu
Keyword(s):  
High Resolution ◽  
Monitoring System ◽  
Super Resolution ◽  
Construction Site ◽  
Construction Monitoring ◽  
Promising Tool ◽  
Engineering Environment ◽  
High Resolution Images ◽  
Public Dataset ◽  
Sr Reconstruction

The degrading of input images due to the engineering environment decreases the performance of helmet detection models so as to prevent their application in practice. To overcome this problem, we propose an end-to-end helmet monitoring system, which implements a super-resolution (SR) reconstruction driven helmet detection workflow to detect helmets for monitoring tasks. The monitoring system consists of two modules, the super-resolution reconstruction module and the detection module. The former implements the SR algorithm to produce high-resolution images, the latter performs the helmet detection. Validations are performed on both a public dataset as well as the realistic dataset obtained from a practical construction site. The results show that the proposed system achieves a promising performance and surpasses the competing methods. It will be a promising tool for construction monitoring and is easy to be extended to corresponding tasks.

Improved Algorithm for High-Resolution Image Stitching Based on ORB Features

2021 ◽  
Vol 58 (8) ◽  
pp. 0810004
Author(s):  
刘天赐 Liu Tianci ◽  
宋延嵩 Song Yansong ◽  
李金旺 Li Jinwang ◽  
赵馨 Zhao Xin
Keyword(s):  
High Resolution ◽  
Image Stitching ◽  
Resolution Image ◽  
High Resolution Image ◽  
Improved Algorithm
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