Publication Details

3D Reconstruction Quality Analysis and Its Acceleration on GPU Clusters

POLOK, L.; ILA, V.; SMRŽ, P. 3D Reconstruction Quality Analysis and Its Acceleration on GPU Clusters. In Proceedings of European Signal Processing Conference 2016. Budapest: Institute of Electrical and Electronics Engineers, 2016. p. 1108-1112. ISBN: 978-0-9928626-6-4.
Czech title
Analýza kvality 3D rekonstrukce její akcelerace na GPU klustrech
Type
conference paper
Language
English
Authors
Polok Lukáš, Ing., Ph.D.
Ila Viorela Simona, Ph.D.
Smrž Pavel, doc. RNDr., Ph.D. (DCGM)
Keywords

bundle adjustment, nonlinear least squares, Schur complement, matrix inverse, marginal covariances

Abstract

3D reconstruction has a wide variety of applications in computer graphics, robotics or digital cinema production, among others. With the rapid increase in computing power, it has become more feasible for the reconstruction algorithms to run online, even on mobile devices. Maximum likelihood estimation (MLE) is the adopted technique to deal with the sensor uncertainty. Most of the existing 3D reconstruction frameworks only recover the mean of the reconstructed geometry. Recovering also the variance is highly computationally intensive and is seldom performed. However, variance is the natural choice of estimate quality indicator. In this paper, the associated costs are analyzed and efficient but exact solutions to calculating partial matrix inverses are proposed, which apply to any general problem with many mutually independent variables. Speedups exceeding an order of magnitude are reported.

Published
2016
Pages
1108–1112
Proceedings
Proceedings of European Signal Processing Conference 2016
ISBN
978-0-9928626-6-4
Publisher
Institute of Electrical and Electronics Engineers
Place
Budapest
DOI
10.1109/EUSIPCO.2016.7760420
UT WoS
000391891900475
EID Scopus
2-s2.0-85006008098
BibTeX 
@inproceedings{BUT130987,
  author="Lukáš {Polok} and Viorela Simona {Ila} and Pavel {Smrž}",
  title="3D Reconstruction Quality Analysis and Its Acceleration on GPU Clusters",
  booktitle="Proceedings of European Signal Processing Conference 2016",
  year="2016",
  pages="1108--1112",
  publisher="Institute of Electrical and Electronics Engineers",
  address="Budapest",
  doi="10.1109/EUSIPCO.2016.7760420",
  isbn="978-0-9928626-6-4"
}
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