Open source structure-from-motion for aerial video

Author(s):  
Matthew J. Leotta ◽  
Eric Smith ◽  
Matthew Dawkins ◽  
Paul Tunison
2020 ◽  
Vol 52 ◽  
pp. 55-61
Author(s):  
Ettore Potente ◽  
Cosimo Cagnazzo ◽  
Alessandro Deodati ◽  
Giuseppe Mastronuzzi

2020 ◽  
Vol 60 (4) ◽  
pp. 288-302 ◽  
Author(s):  
Adam Dlesk ◽  
Karel Vach ◽  
Karel Pavelka

SfM processing of archived analogue images gives an opportunity to efficiently create new and valuable 2D and 3D results. The SfM processing of digitized analogue images brings some challenges. How to digitize negatives of photogrammetric images? What scanning resolution is the most beneficial for processing? How to preprocess the digitized images to be able to process them using the SfM method? What accuracy of results is possible to expect? This paper tries to deal with all these questions. For this paper, 7 negatives of former photogrammetric documentation of a vault were chosen. The negatives were captured by Rollei 3003 metric camera in 1999. Two pieces of software were chosen for the SfM processing. A commercial alternative Agisoft PhotoScan and free open-source alternative MicMac. The results of the SfM processing were compared to the results of an original photogrammetric method, which was used for former processing in 1999.


Author(s):  
D. González-Aguilera ◽  
E. Ruiz de Oña ◽  
L. López-Fernandez ◽  
E. M. Farella ◽  
E. K. Stathopoulou ◽  
...  

Abstract. Automatic feature matching is a crucial step in Structure-from-Motion (SfM) applications for 3D reconstruction purposes. From an historical perspective we can say now that SIFT was the enabling technology that made SfM a successful and fully automated pipeline. SIFT was the ancestor of a wealth of detector/descriptor methods that are now available. Various research activities have tried to benchmark detector/descriptors operators, but a clear outcome is difficult to be drawn. This paper presents an ISPRS Scientific Initiative aimed at providing the community with an educational open-source tool (called PhotoMatch) for tie point extractions and image matching. Several enhancement and decolorization methods can be initially applied to an image dataset in order to improve the successive feature extraction steps. Then different detector/descriptor combinations are possible, coupled with different matching strategies and quality control metrics. Examples and results show the implemented functionality of PhotoMatch which has also a tutorial for shortly explaining the implemented methods.


Author(s):  
Utkarsh Srivastava ◽  
Ramanathan L.

Diabetes Mellitus has turned into a noteworthy general wellbeing issue in India. Most recent measurements on diabetes uncover that 63 million individuals in India are experiencing diabetes, and this figure is probably going to go up to 80 million by 2025. Given the rise of big data as a socio-technical phenomenon, there are various complications in analyzing big data and its related data handling issues. This chapter examines Hadoop, an open source structure that permits the disseminated handling for huge datasets on group of PCs and thus finally produces better results with the deployment of Iterative MapReduce. The goal of this chapter is to dissect and extricate the enhanced performance of data analysis in distributed environment. Iterative MapReduce (i-MapReduce) plays a major role in optimizing the analytics performance. Implementation is done on Cloudera Hadoop introduced on top of Hortonworks Data Platform (HDP) Sandbox.


Author(s):  
Jonathan Lisein ◽  
Nathalie Pineux ◽  
Marc Pierrot-Deseilligny ◽  
Aurore Degré ◽  
Philippe Lejeune

L'émergence des drones comme outils de cartographie rapide, de par leur capacité à répondre à des besoins trèsspécifiques, offre de nombreuses opportunités aux scientifiques. Par ailleurs, les récentes évolutions des techniques dephotogrammétrie et de vision par ordinateur permettent, à partir de prises de vues aériennes stéréoscopiques, de fourniraux géomorphologues et aux hydrologues des données topographiques à haute résolution (Tarolli, 2014). En effet, lesalgorithmes d'orientation externe (structure from motion en anglais, Snavely et al. (2008)) permettent la déterminationautomatique de la position et de l'orientation des prises de vue d'une collection d'images se recouvrant. La corrélationdense automatique permet ensuite, depuis un bloc d'images orientées, de modéliser finement le relief. L'utilisation engéomorphologie de drones pour la modélisation du relief en est encore à ses premiers souffles, mais montre un potentieltrès intéressant. La précision des mesures photogrammétriques rivalise en effet avec les relevés LiDAR, pour un coûtd'acquisition significativement moins élevé. Cette recherche se focalise sur deux objectifs. Le premier est de déterminersi la précision des mesures photogrammétriques issues d'images acquises avec un mini-drone permet la détection dechangement de relief très fin via la comparaison d'acquisitions multi-dates. Le deuxième objectif, plus spécifique, est dedéterminer la manière la plus optimale de paramétrer la compensation par faisceaux avec points d'appui au sein de la suitephotogrammétrique open-source MICMAC.


Sign in / Sign up

Export Citation Format

Share Document