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Intercomparison of photogrammetry software for three-dimensional vegetation modelling
Author(s) -
Alexandra S. Probst,
Demetrios Gatziolis,
Nikolay Strigul
Publication year - 2018
Publication title -
royal society open science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.84
H-Index - 51
ISSN - 2054-5703
DOI - 10.1098/rsos.172192
Subject(s) - photogrammetry , computer science , software , expediting , a priori and a posteriori , remote sensing , field (mathematics) , vegetation (pathology) , artificial intelligence , data mining , geology , mathematics , systems engineering , medicine , pathology , programming language , philosophy , epistemology , pure mathematics , engineering
Photogrammetry-based three-dimensional reconstruction of objects is becoming increasingly appealing in research areas unrelated to computer vision. It has the potential to facilitate the assessment of forest inventory-related parameters by enabling or expediting resource measurements in the field. We hereby compare several implementations of photogrammetric algorithms (CMVS/PMVS, CMPMVS, MVE, OpenMVS, SURE and Agisoft PhotoScan) with respect to their performance in vegetation assessment. The evaluation is based on (i) a virtual scene where the precise location and dimensionality of objects is known a priori and is thus conducive to a quantitative comparison and (ii) using series of in situ acquired photographs of vegetation with overlapping field of view where the photogrammetric outcomes are compared qualitatively. Performance is quantified by computing receiver operating characteristic curves that summarize the type-I and type-II errors between the reference and reconstructed tree models. Similar artefacts are observed in synthetic- and in situ -based reconstructions.

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