Paper Info
Title
Accurate 3D surface measurement of mountain slopes through a fully automated image-based technique.
Abstract
In this paper an automated procedure for surface reconstruction that can be used for surveying and monitoring rock and ground slopes is presented. This method has been developed for geological and engineering applications, where accuracy and completeness are factors of primary importance for the final 3D model, which must provide a detailed metric survey and not only a visual reconstruction of the scene. The proposed procedure integrates two image matching techniques. The first one is used to automatically extract a set of tie points that are needed for computing the exterior orientation parameters of all images through a photogrammetric bundle adjustment. Such tie oints are also exploited to obtain a preliminary seed model that is then enriched based on Multi-photo Least Squares Matching. During this second stage, the surface model is improved in terms of point density and accuracy. Different strategies were implemented to successfully combine both techniques, along with some new improvements. The presented procedure has been tested in two different applications: geometric modelling of rock cliffs and evaluation of weathering of a ground slope. In both cases the obtained results presented accuracy sufficient for geological investigation. Moreover, outcomes were comparable to the ones from laser scanning surveying and other photogrammetric implementations.
Year
DOI
Venue
2014
10.1007/s12145-014-0158-2
Earth Science Informatics
Keywords
Field
DocType
Slope reconstruction, Image matching, Photogrammetry, Feature extraction
Photogrammetry,Surface reconstruction,Computer vision,Laser scanning,Bundle adjustment,Computer science,Image matching,Remote sensing,Feature extraction,Geometric design,Artificial intelligence,Completeness (statistics)
Journal
Volume
Issue
ISSN
7
2
1865-0481
Citations 
PageRank 
References 
4
0.55
9
Authors
3
Name
Order
Citations
PageRank
Mattia Previtali1266.07
Luigi Barazzetti23911.39
Marco Scaioni39716.34