Collaborative Mobile 3D Reconstruction of Urban Scenes

2015 ◽  
pp. 486-501 ◽  
Author(s):  
Attila Tanács ◽  
András Majdik ◽  
Levente Hajder ◽  
József Molnár ◽  
Zsolt Sánta ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Urban Scenes

scholarly journals EXPLORING THE APPLICABILITY OF SEMI-GLOBAL MATCHING FOR SAR-OPTICAL STEREOGRAMMETRY OF URBAN SCENES

2018 ◽  
Vol XLII-2 ◽  
pp. 43-48 ◽  
Author(s):  
H. Bagheri ◽  
M. Schmitt ◽  
P. d’Angelo ◽  
X. X. Zhu
Keyword(s):  
3D Reconstruction ◽  
Optical Image ◽  
Urban Scenes ◽  
Multiple Sensors ◽  
Limited Applicability ◽  
Global Matching ◽  
Satellite Sensors ◽  
Sar Imagery ◽  
Image Pairs ◽  
3D Information

Nowadays, a huge archive of data from different satellite sensors is available for diverse objectives. While every new sensor provides data with ever higher resolution and more sophisticated special properties, using the data acquired by only one sensor might sometimes still not be enough. As a result, data fusion techniques can be applied with the aim of jointly exploiting data from multiple sensors. One example is to produce 3D information from optical and SAR imagery by employing stereogrammetric methods. This paper investigates the application of the semi-global matching (SGM) framework for 3D reconstruction from SAR-optical image pairs. For this objective, first a multi-sensor block adjustment is carried out to align the optical image with a corresponding SAR image using an RPC-based formulation of the imaging models. Then, a dense image matching, SGM is implemented to investigate its potential for multi-sensor 3D reconstruction. While the results achieved with Worldview-2 and TerraSAR-X images demonstrate the general feasibility of SARoptical stereogrammetry, they also show the limited applicability of SGM for this task in its out-of-the-box formulation.

Efficient 3D Reconstruction for Urban Scenes

2013 ◽  
pp. 546-555 ◽  
Author(s):  
Weichao Fu ◽  
Lin Zhang ◽  
Hongyu Li ◽  
Xinfeng Zhang ◽  
Di Wu
Keyword(s):  
3D Reconstruction ◽  
Urban Scenes

scholarly journals Sampling-Based Path Planning for High-Quality Aerial 3D Reconstruction of Urban Scenes

2021 ◽  
Vol 13 (5) ◽  
pp. 989
Author(s):  
Feihu Yan ◽  
Enyong Xia ◽  
Zhaoxin Li ◽  
Zhong Zhou
Keyword(s):  
Path Planning ◽  
3D Reconstruction ◽  
Flight Control ◽  
Large Scale ◽  
Simulated Data ◽  
Urban Environments ◽  
High Quality ◽  
Aerial Photos ◽  
Urban Scenes ◽  
Extensive Evaluation

Unmanned aerial vehicles (UAVs) can capture high-quality aerial photos and have been widely used for large-scale urban 3D reconstruction. However, even with the help of commercial flight control software, it is still a challenging task for non-professional users to capture full-coverage aerial photos in complex urban environments, which normally leads to incomplete 3D reconstruction. In this paper, we propose a novel path planning method for the high-quality aerial 3D reconstruction of urban scenes. The proposed approach first captures aerial photos, following an initial path to generate a coarse 3D model as prior knowledge. Then, 3D viewpoints with constrained location and orientation are generated and evaluated, according to the completeness and accuracy of the corresponding visible regions of the prior model. Finally, an optimized path is produced by smoothly connecting the optimal viewpoints. We perform an extensive evaluation of our method on real and simulated data sets, in comparison with a state-of-the-art method. The experimental results indicate that the optimized trajectory generated by our method can lead to a significant boost in the performance of aerial 3D urban reconstruction.

IMGTR: Image-triangle based multi-view 3D reconstruction for urban scenes

2021 ◽  
Vol 181 ◽  
pp. 191-204
Author(s):  
Zhihua Hu ◽  
Yaolin Hou ◽  
Pengjie Tao ◽  
Jie Shan
Keyword(s):  
3D Reconstruction ◽  
Urban Scenes

Localization and 3D reconstruction of urban scenes using GPS

2008 ◽  
Author(s):  
Kihwan Kim ◽  
Jay Summet ◽  
Thad Starner ◽  
Daniel Ashbrook ◽  
Mrunal Kapade ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Urban Scenes

scholarly journals AUTOMATED CHAIN FOR LARGE-SCALE 3D RECONSTRUCTION OF URBAN SCENES FROM SATELLITE IMAGES

2019 ◽  
Vol XLII-2/W16 ◽  
pp. 243-250
Author(s):  
S. Tripodi ◽  
L. Duan ◽  
F. Trastour ◽  
V. Poujad ◽  
L. Laurore ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Large Scale ◽  
Satellite Images ◽  
Digital Terrain Model ◽  
Stereo Pair ◽  
Convolutional Network ◽  
Urban Scenes ◽  
Terrain Model ◽  
Digital Terrain ◽  
City Modeling

<p><strong>Abstract.</strong> Automatic city modeling from satellite imagery is a popular yet challenging topic in remote sensing, driven by numerous applications such as telecommunications, defence and urban mamagement. In this paper, we present an automated chain for large-scale 3D reconstruction of urban scenes with a Level of Detail 1 from satellite images. The proposed framework relies on two key ingredient. First, from a stereo pair of images, we estimate a digital terrain model and a digital height model, by using a novel set of feature descriptors based on multiscale morphological analysis. Second, inspired by recent works in machine learning, we extract in an automatic way contour polygons of buildings, by adopting a fully convolutional network U-Net followed by a polygonization of the predicted mask of buildings. We demonstrate the potential of our chain by reconstructing in an automated way different areas of the world.</p>

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