@inproceedings{48b17b8c395147d5a561f7a3fb17a6d7,
title = "Fast incremental bundle adjustment with covariance recovery",
abstract = "Efficient 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 efficient 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 efficiency of the incremental BA solver for long camera trajectory applications, and provides extremely fast covariance recovery.",
keywords = "Bundle-Adjustment, Incremental-Solvers, Schur-Complement, Structure-from-Motion",
author = "Viorela Ila and Lukas Polok and Marek Solony and Klemen Istenic",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 7th IEEE International Conference on 3D Vision, 3DV 2017 ; Conference date: 10-10-2017 Through 12-10-2017",
year = "2018",
month = may,
day = "25",
doi = "10.1109/3DV.2017.00029",
language = "English",
series = "Proceedings - 2017 International Conference on 3D Vision, 3DV 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "175--184",
booktitle = "Proceedings - 2017 International Conference on 3D Vision, 3DV 2017",
address = "United States",
}