scholarly journals UAV LINEAR PHOTOGRAMMETRY

2015 ◽  
Vol XL-3/W3 ◽  
pp. 327-333 ◽  
Author(s):  
V. Tournadre ◽  
M. Pierrot-Deseilligny ◽  
P. H. Faure
Keyword(s):  
Open Source ◽  
Ground Truth ◽  
3D Models ◽  
Bundle Adjustment ◽  
Acquisition Process ◽  
Calibration Models ◽  
All Solutions ◽  
Oblique Images ◽  
Free Open Source ◽  
Terrestrial Photogrammetry

The photogrammetric treatment of images acquired on a linear axis is a problematic case. Such tricky configurations often leads to bended 3D models, described as a bowl effect, which requires ground measurements to be fixed. This article presents different solutions to overcome that problem. All solutions have been implemented into the free open-source photogrammetric suite MicMac. The article presents the lasts evolutions of MicMac's bundle adjustment core, as well as some extended calibration models and how they fit for the camera evaluated. The acquisition process is optimized by presenting how oblique images can improve the accuracy of the orientations, while the 3D models accuracies are assessed by producing a millimeter accurate ground truth from terrestrial photogrammetry.

scholarly journals REFINED SATELLITE IMAGE ORIENTATION IN THE FREE OPEN-SOURCE PHOTOGRAMMETRIC TOOLS APERO/MICMAC

2016 ◽  
Vol III-1 ◽  
pp. 83-90 ◽  
Author(s):  
E. Rupnik ◽  
M. Pierrot Deseilligny ◽  
A. Delorme ◽  
Y. Klinger
Keyword(s):  
Open Source ◽  
Satellite Image ◽  
Bundle Adjustment ◽  
Physical Constraint ◽  
Adjustment Model ◽  
Triplet Pair ◽  
Image Orientation ◽  
Free Open Source

This publication presents the RPC-based bundle adjustment implemented in the freeware open-source photogrammetric tool Apero/MicMac. The bundle adjustment model is based on some polynomial correction functions, enriched with a physical constraint that introduces the notion of a global sensor rotation into the model. The devised algorithms are evaluated against two datasets consisting of two stereo and a triplet pair of the Pleiades images. Two sets of correction functions and a number of GCPs configurations are examined. The obtained geo-referencing accuracy falls below the size of 1GSD.

scholarly journals METRIC EVALUATION PIPELINE FOR 3D MODELING OF URBAN SCENES

2017 ◽  
Vol XLII-1/W1 ◽  
pp. 239-246 ◽  
Author(s):  
M. Bosch ◽  
A. Leichtman ◽  
D. Chilcott ◽  
H. Goldberg ◽  
M. Brown
Keyword(s):  
Open Source ◽  
Satellite Imagery ◽  
3D Modeling ◽  
Ground Truth ◽  
3D Models ◽  
Airborne Lidar ◽  
Perceptual Quality ◽  
Urban Scenes ◽  
Sensing Applications ◽  
3D Point Clouds

Publicly available benchmark data and metric evaluation approaches have been instrumental in enabling research to advance state of the art methods for remote sensing applications in urban 3D modeling. Most publicly available benchmark datasets have consisted of high resolution airborne imagery and lidar suitable for 3D modeling on a relatively modest scale. To enable research in larger scale 3D mapping, we have recently released a public benchmark dataset with multi-view commercial satellite imagery and metrics to compare 3D point clouds with lidar ground truth. We now define a more complete metric evaluation pipeline developed as publicly available open source software to assess semantically labeled 3D models of complex urban scenes derived from multi-view commercial satellite imagery. Evaluation metrics in our pipeline include horizontal and vertical accuracy and completeness, volumetric completeness and correctness, perceptual quality, and model simplicity. Sources of ground truth include airborne lidar and overhead imagery, and we demonstrate a semi-automated process for producing accurate ground truth shape files to characterize building footprints. We validate our current metric evaluation pipeline using 3D models produced using open source multi-view stereo methods. Data and software is made publicly available to enable further research and planned benchmarking activities.

scholarly journals REFINED SATELLITE IMAGE ORIENTATION IN THE FREE OPEN-SOURCE PHOTOGRAMMETRIC TOOLS APERO/MICMAC

2016 ◽  
Vol III-1 ◽  
pp. 83-90 ◽  
Author(s):  
E. Rupnik ◽  
M. Pierrot Deseilligny ◽  
A. Delorme ◽  
Y. Klinger
Keyword(s):  
Open Source ◽  
Satellite Image ◽  
Bundle Adjustment ◽  
Physical Constraint ◽  
Adjustment Model ◽  
Triplet Pair ◽  
Image Orientation ◽  
Free Open Source

This publication presents the RPC-based bundle adjustment implemented in the freeware open-source photogrammetric tool Apero/MicMac. The bundle adjustment model is based on some polynomial correction functions, enriched with a physical constraint that introduces the notion of a global sensor rotation into the model. The devised algorithms are evaluated against two datasets consisting of two stereo and a triplet pair of the Pleiades images. Two sets of correction functions and a number of GCPs configurations are examined. The obtained geo-referencing accuracy falls below the size of 1GSD.

scholarly journals RobotP: A Benchmark Dataset for 6D Object Pose Estimation

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1299
Author(s):  
Honglin Yuan ◽  
Tim Hoogenkamp ◽  
Remco C. Veltkamp
Keyword(s):  
Pose Estimation ◽  
Ground Truth ◽  
3D Models ◽  
Depth Image ◽  
Great Success ◽  
Estimation Algorithms ◽  
Depth Images ◽  
Object Pose Estimation ◽  
Image Pairs ◽  
Bounding Boxes

Deep learning has achieved great success on robotic vision tasks. However, when compared with other vision-based tasks, it is difficult to collect a representative and sufficiently large training set for six-dimensional (6D) object pose estimation, due to the inherent difficulty of data collection. In this paper, we propose the RobotP dataset consisting of commonly used objects for benchmarking in 6D object pose estimation. To create the dataset, we apply a 3D reconstruction pipeline to produce high-quality depth images, ground truth poses, and 3D models for well-selected objects. Subsequently, based on the generated data, we produce object segmentation masks and two-dimensional (2D) bounding boxes automatically. To further enrich the data, we synthesize a large number of photo-realistic color-and-depth image pairs with ground truth 6D poses. Our dataset is freely distributed to research groups by the Shape Retrieval Challenge benchmark on 6D pose estimation. Based on our benchmark, different learning-based approaches are trained and tested by the unified dataset. The evaluation results indicate that there is considerable room for improvement in 6D object pose estimation, particularly for objects with dark colors, and photo-realistic images are helpful in increasing the performance of pose estimation algorithms.

scholarly journals Short-term adoption rates for a web-based portal within the intranet of a hospital information system

2019 ◽  
Vol 26 (1) ◽  
pp. e100004 ◽  
Author(s):  
Athanasios Kotoulas ◽  
Ioannis Stratis ◽  
Theodoros Goumenidis ◽  
George Lambrou ◽  
Dimitrios - Dionysios Koutsouris
Keyword(s):  
Open Source ◽  
Resistance To Change ◽  
Content Management ◽  
Healthcare Management ◽  
Short Term ◽  
Web Based ◽  
Average Growth ◽  
Greek Hospital ◽  
Set Up ◽  
Free Open Source

ObjectiveAn intranet portal that combines cost-free, open-source software technology with easy set-up features can be beneficial for daily hospital processes. We describe the short-term adoption rates of a costless content management system (CMS) in the intranet of a tertiary Greek hospital.DesignDashboard statistics of our CMS platform were the implementation assessment of our system.ResultsIn a period of 10 months of running the software, the results indicate the employees overcame ‘Resistance to Change’ status. The average growth rate of end users who exploit the portal services is calculated as 2.73 every 3.3 months.ConclusionWe found our intranet web-based portal to be acceptable and helpful so far. Exploitation of an open-source CMS within the hospital intranet can influence healthcare management and the employees’ way of working as well.

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