2017
DOI: 10.5194/isprs-archives-xlii-2-w5-591-2017
|View full text |Cite
|
Sign up to set email alerts
|

A Critical Review of Automated Photogrammetric Processing of Large Datasets

Abstract: ABSTRACT:The paper reports some comparisons between commercial software able to automatically process image datasets for 3D reconstruction purposes. The main aspects investigated in the work are the capability to correctly orient large sets of image of complex environments, the metric quality of the results, replicability and redundancy. Different datasets are employed, each one featuring a diverse number of images, GSDs at cm and mm resolutions, and ground truth information to perform statistical analyses of … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

1
97
0
4

Year Published

2017
2017
2022
2022

Publication Types

Select...
6
2

Relationship

1
7

Authors

Journals

citations
Cited by 121 publications
(102 citation statements)
references
References 26 publications
(31 reference statements)
1
97
0
4
Order By: Relevance
“…These studies have also made it possible to compare the peculiarities and specificities of the different procedures, with the possibility to obtain the maximum benefit from current hardware and software technologies (Remondino et al, 2017). The various experiments have led to significant developments in terms of precision, accuracy, costs, acquisition times and data processing (Remondino, et al 2014;Apollonio et al, 2014;Fassi, et al, 2013).…”
Section: Related Work and Aimsmentioning
confidence: 99%
“…These studies have also made it possible to compare the peculiarities and specificities of the different procedures, with the possibility to obtain the maximum benefit from current hardware and software technologies (Remondino et al, 2017). The various experiments have led to significant developments in terms of precision, accuracy, costs, acquisition times and data processing (Remondino, et al 2014;Apollonio et al, 2014;Fassi, et al, 2013).…”
Section: Related Work and Aimsmentioning
confidence: 99%
“…Consequently, the updating of point clouds is an expensive process. But, with the improvement of RGB cameras performance during the last few years (Nocerino, 2017, Masiero, 2106, the use of imagederived point clouds has become a suitable alternative. The use of these point clouds has the advantage of dramatically reducing the cost of point cloud updating without losing density and accuracy ( Figure 4).…”
Section: Introductionmentioning
confidence: 99%
“…The SfM approach (Schönberger and Frahm, 2016) is an efficient and robust technique for obtaining 3D models or point clouds using smartphone camera imagery (Nocerino, 2017), (Golodetz, 2018). The absolute scale and the proper georeferencing of the 3D models can be achieved using Ground Control, GNSS tagged images, or a combination of both.…”
Section: Introductionmentioning
confidence: 99%
“…The raw dense point cloud is then further processed to obtain a mesh with photographic texture mapped on it, typically at full image resolution (Remondino et al, 2013;Menna et al, 2012).…”
Section: General Digitization Procedures Using a Turntablementioning
confidence: 99%
“…Various investigations (Wenzel et al, 2013;GonizziBarsanti et al, 2014;Toschi et al, 2014;Macher et al, 2017) demonstrated that, with respect to other methods, automation in image-based methods has reached a very efficient level in various application projects, with great potentials. Beside some processing open issues (Nocerino et al, 2014;Menna et al, 2016;Remondino et al, 2017), image acquisition is still a very crucial step, limiting the quality of the final 3D results. Particularly, in case of mass heritage 3D digitization projects (Europeana; Google Art Project; Santos et al, 2017aSantos et al, , 2017b or complex objects with non-collaborative surfaces, the whole 3D digitization pipeline based on a manual image acquisition followed by an offline processing may be not cost effective.…”
Section: Introductionmentioning
confidence: 99%