FN Archimer Export Format
PT J
TI Scale Accuracy Evaluation of Image-Based 3D Reconstruction Strategies Using Laser Photogrammetry
BT 
AF Istenič, Klemen
   Gracias, Nuno
   Arnaubec, Aurelien
   Escartín, Javier
   Garcia, Rafael
AS 1:1,2;2:1;3:3;4:4;5:1;
FF 1:;2:;3:PDG-DFO-SM-PRAO;4:;5:;
C1 Underwater Robotics Research Center (CIRS), Computer Vision and Robotics Institute (VICOROB), University of Girona, Edifici P-IV, Campus de Montilivi, 17071 Girona, Spain
   Coronis Computing, S.L., Science and Technological Park of UdG, Carrer Pic de Peguera, 15, 17003 Girona, Spain
   IFREMER, Centre Méditerranée, Unité Syst. Marins, CS 20330, F-83507 La Seyne Sur Mer, France
   Université de Paris, Institut de Physique du Globe de Paris, CNRS, F-75005 Paris, France
C2 UNIV GIRONA, SPAIN
   CORONIS COMPUTING, SPAIN
   IFREMER, FRANCE
   IPGP, FRANCE
SI TOULON
SE PDG-DFO-SM-PRAO
IN WOS Ifremer UPR
   DOAJ
   copubli-france
   copubli-europe
IF 2.1
TC 13
UR https://archimer.ifremer.fr/doc/00515/62643/67020.pdf
LA English
DT Article
CR ODEMAR
   SUBSAINTES
BO Pourquoi pas ?
   L'Atalante
DE ;photogrammetry;metrology;underwater 3D reconstruction;structure-from-motion;navigation fusion;multiobjective BA;laser scalers;Monte Carlo simulation;uncertainty estimation;scale drift evaluation;laser spot detection
AB Rapid developments in the field of underwater photogrammetry have given scientists the ability to produce accurate 3-dimensional (3D) models which are now increasingly used in the representation and study of local areas of interest. This paper addresses the lack of systematic analysis of 3D reconstruction and navigation fusion strategies, as well as associated error evaluation of models produced at larger scales in GPS-denied environments using a monocular camera (often in deep sea scenarios). Based on our prior work on automatic scale estimation of Structure from Motion (SfM)-based 3D models using laser scalers, an automatic scale accuracy framework is presented. The confidence level for each of the scale error estimates is independently assessed through the propagation of the uncertainties associated with image features and laser spot detections using a Monte Carlo simulation. The number of iterations used in the simulation was validated through the analysis of the final estimate behavior. To facilitate the detection and uncertainty estimation of even greatly attenuated laser beams, an automatic laser spot detection method was developed, with the main novelty of estimating the uncertainties based on the recovered characteristic shapes of laser spots with radially decreasing intensities. The effects of four different reconstruction strategies resulting from the combinations of Incremental/Global SfM, and the a priori and a posteriori use of navigation data were analyzed using two distinct survey scenarios captured during the SUBSAINTES 2017 cruise (doi: 10.17600/17001000). The study demonstrates that surveys with multiple overlaps of nonsequential images result in a nearly identical solution regardless of the strategy (SfM or navigation fusion), while surveys with weakly connected sequentially acquired images are prone to produce broad-scale deformation (doming effect) when navigation is not included in the optimization. Thus the scenarios with complex survey patterns substantially benefit from using multiobjective BA navigation fusion. The errors in models, produced by the most appropriate strategy, were estimated at around 1% in the central parts and always inferior to 5% on the extremities. The effects of combining data from multiple surveys were also evaluated. The introduction of additional vectors in the optimization of multisurvey problems successfully accounted for offset changes present in the underwater USBL-based navigation data, and thus minimize the effect of contradicting navigation priors. Our results also illustrate the importance of collecting a multitude of evaluation data at different locations and moments during the survey. 
PY 2019
PD SEP
SO Remote Sensing
SN 2072-4292
PU MDPI AG
VL 11
IS 18
UT 000489101500023
DI 10.3390/rs11182093
ID 62643
ER

EF