Development of an All-Purpose Free Photogrammetric Tool

González‐Aguilera, Diego; López-Fernández, Luis Andrés; Rodríguez‐Gonzálvez, Pablo; Guerrero, David; Hernández-López, David; Remondino, Fabio; Menna, Fabio; Nocerino, Erica; Toschi, I.; Ballabeni, Andrea; Gaiani, Marco

doi:10.5194/isprs-archives-xli-b6-31-2016

Cited by 30 publications

(23 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The resulting point clouds were obtained from the photogrammetric processing based on dense matching and using GRAPHOS software [12]. The results are outlined in Figure 3. …”

Section: Computational Performance Analysismentioning

confidence: 99%

“…In addition, LiDAR technology encloses a number of significant technical limitations such as the effective measurement acquisition range, acquisition rate (density), precision, and high cost. On the contrary, modern photogrammetry and dense matching techniques [12] provide better resolution than LiDAR (one depth or one elevation is generated per pixel), although they require a high photogrammetric computational cost. In any case, both LiDAR and photogrammetric point clouds require the extraction of relevant and useful information beyond their own point cloud.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Comparative Analysis of Triangulation Libraries for Modeling Large Point Clouds from Land and Their Infrastructures

et al. 2017

View full text Add to dashboard Cite

Abstract:Although the generation of large points clouds from geomatic techniques allows us to realize the topography and appearance of the terrain and its infrastructures (e.g., roads, bridges, buildings, etc.), all these 3D point clouds require an unavoidable step to be conveniently treated: the definition of the surface that connects these points in space through digital surface models (DSM). In addition, these point clouds sometimes have associated attributes and geometric constraints such as breaklines and/or exclusion areas, which require the implementation of efficient triangulation techniques that can cope with a high volume of information. This article aims to make a comparative analysis of different Delaunay triangulation libraries, open or with academic versions available for the scientific community, so that we can assess their suitability for the modeling of the territory and its infrastructures. The comparison was carried out from a two-fold perspective: (i) to analyze and compare the computational cost of the triangulation; (ii) to assess the geometric quality of the resulting meshes. The different techniques and libraries have been tested based on three different study cases and the corresponding large points clouds generated. The study has been useful to identify the limitations of the existing large point clouds triangulation libraries and to propose statistical variables that assess the geometric quality of the resulting DSM.

show abstract

“…The resulting point clouds were obtained from the photogrammetric processing based on dense matching and using GRAPHOS software [12]. The results are outlined in Figure 3. …”

Section: Computational Performance Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Triangulation Libraries for Modeling Large Point Clouds from Land and Their Infrastructures

et al. 2017

View full text Add to dashboard Cite

show abstract

“…Other popular solutions include Pix4D, Photomodeler, RealityCapture and 3DF Zephyr [39,44] [42], the ISPRS Scientific Initiative project GRAPHOS [17] or VisualSFM [45]. Partial algorithms and software programs performing a specific part of the general photogrammetric workflow also exist, for example DBAT [21], which calculates the bundle adjustment step, and SURE [46], which generates 3D dense point clouds from pre-oriented images.…”

Section: Software Solutionsmentioning

confidence: 99%

“…Despite the presence of many open source solutions [16,17], commercial solutions remain very popular among users [18,19], especially outside the photogrammetric community. This is mainly due to the fact that commercial solutions tend to provide fairly accurate results with simpler and more streamlined user interfaces.…”

Section: Introductionmentioning

confidence: 99%

Open Source and Independent Methods for Bundle Adjustment Assessment in Close-Range UAV Photogrammetry

Murtiyoso

Grussenmeyer

Börlin

et al. 2018

Drones

View full text Add to dashboard Cite

Close-range photogrammetry as a technique to acquire reality-based 3D data has, in recent times, seen a renewed interest due to developments in sensor technologies. Furthermore, the strong democratization of UAVs (Unmanned Aerial Vehicles) or drones means that close-range photogrammetry can now be used as a viable low-cost method for 3D mapping. In terms of software development, this led to the creation of many commercial black-box solutions (PhotoScan, Pix4D, etc.). This paper aims to demonstrate how the open source toolbox DBAT (Damped Bundle Adjustment Toolbox) can be used to generate detailed photogrammetric network diagnostics to help assess the quality of surveys processed by the commercial software, PhotoScan. In addition, the Apero module from the MicMac software suite was also used to provide an independent assessment of the results. The assessment is performed by the careful examination of some of the bundle adjustment metrics generated by both open source solutions. A UAV project was conducted on a historical church in the city center of Strasbourg, France, in order to provide a dataset with a millimetric level of precision. Results showed that DBAT can be used to reprocess PhotoScan projects under similar conditions and derive useful metrics from them, while Apero provides a completely independent verification of the results of commercial solutions. Overall, this paper shows that an objective assessment of photogrammetric results is important. In cases where problems are encountered in the project, this assessment method can be useful to detect errors that may not be explicitly presented by PhotoScan.

show abstract

“…Thus, the computation of the thermophysical properties of PV modules or their precise absolute temperature is not necessary and the accurate location of the pathologies is performed through a custom 5D metric product. In this case, images from the RGB cameras are processed with photogrammetric and computer vision algorithms [38,39] for their orientation and generation of a 3D dense point cloud of the PV panels.…”

Section: Introductionmentioning

confidence: 99%

Automatic Evaluation of Photovoltaic Power Stations from High-Density RGB-T 3D Point Clouds

et al. 2017

View full text Add to dashboard Cite

A low-cost unmanned aerial platform (UAV) equipped with RGB (Red, Green, Blue) and thermographic sensors is used for the acquisition of all the data needed for the automatic detection and evaluation of thermal pathologies on photovoltaic (PV) surfaces and geometric defects in the mounting on photovoltaic power stations. RGB imagery is used for the generation of a georeferenced 3D point cloud through digital image preprocessing, photogrammetric and computer vision algorithms. The point cloud is complemented with temperature values measured by the thermographic sensor and with intensity values derived from the RGB data in order to obtain a multidimensional product (5D: 3D geometry plus temperature and intensity on the visible spectrum). A segmentation workflow based on the proper integration of several state-of-the-art geomatic and mathematic techniques is applied to the 5D product for the detection and sizing of thermal pathologies and geometric defects in the mounting in the PV panels. It consists of a three-step segmentation procedure, involving first the geometric information, then the radiometric (RGB) information, and last the thermal data. No configuration of parameters is required. Thus, the methodology presented contributes to the automation of the inspection of PV farms, through the maximization of the exploitation of the data acquired in the different spectra (visible and thermal infrared bands). Results of the proposed workflow were compared with a ground truth generated according to currently established protocols and complemented with a topographic survey. The proposed methodology was able to detect all pathologies established by the ground truth without adding any false positives. Discrepancies in the measurement of damaged surfaces regarding established ground truth, which can reach the 5% of total panel surface for the visual inspection by an expert operator, decrease with the proposed methodology under the 2%. The geometric evaluation of the facilities presents discrepancies regarding the ground truth lower than one degree for angular parameters (azimuth and tilt) and lower than 0.05 m 2 for the area of each solar panel.

show abstract

Development of an All-Purpose Free Photogrammetric Tool

Cited by 30 publications

References 23 publications

Comparative Analysis of Triangulation Libraries for Modeling Large Point Clouds from Land and Their Infrastructures

Comparative Analysis of Triangulation Libraries for Modeling Large Point Clouds from Land and Their Infrastructures

Open Source and Independent Methods for Bundle Adjustment Assessment in Close-Range UAV Photogrammetry

Automatic Evaluation of Photovoltaic Power Stations from High-Density RGB-T 3D Point Clouds

Contact Info

Product

Resources

About