Detail výsledku
Fast Incremental Bundle Adjustment with Covariance Recovery
Polok Lukáš, Ing., Ph.D.
Šolony Marek, Ing., Ph.D., UPGM (FIT)
Istenič Klemen
Effcient algorithms exist to obtain a sparse 3D representation of the environment. Bundle adjustment (BA) and structure from motion (SFM) are techniques used to estimate both the camera poses and the set of sparse points in the environment. Many applications require such reconstruction to be performed online, while acquiring the data and produce an updated result every step. Furthermore, using active feedback about the quality of the reconstruction can help selecting the best views to increase the accuracy as well as to maintain a reasonable size of the collected data. This paper provides novel and efcient solutions to solving the associated NLS incrementally, and to compute not only the optimal solution but also the associated uncertainty. The proposed technique highly increases the efciency of the incremental BA solver for long camera trajectory applications and provides extremely fast covariance recovery.
bundle adjustment, incremental, covariance, 3D reconstruction, structure from motion
@inproceedings{BUT144480,
author="Viorela Simona {Ila} and Lukáš {Polok} and Marek {Šolony} and Klemen {Istenič}",
title="Fast Incremental Bundle Adjustment with Covariance Recovery",
booktitle="2017 Fifth International Conference on 3D Vision",
year="2017",
pages="1--9",
publisher="Institute of Electrical and Electronics Engineers",
address="Qingdao",
doi="10.1109/3DV.2017.00029",
isbn="978-989-8425-47-8",
url="https://www.fit.vut.cz/research/publication/11542/"
}