@inproceedings{05e5b32f183e4be29f2efca9fbc7097a,
title = "Direct feature correspondence in vision-aided inertial navigation for unmanned aerial vehicles",
abstract = "This paper proposes a novel method for corresponding visual measurements to map points in a visual-inertial navigation system. The algorithm is based on the minimization of the photometric error on sparse locations of the image region, and realizes a gain in robustness that comes from the elimination of the need of feature-extraction for correspondence. The system is compared to a standard approach based on feature extraction, within a visual-inertial EKF formulation. High-fidelity simulation results show the proposed method improves the horizontal RMS error by means of increasing the number of features corresponded by the algorithm.",
author = "Vall{\'e}s, {Federico Paredes} and Magree, {Daniel P.} and Eric Johnson",
year = "2017",
month = jul,
day = "25",
doi = "10.1109/ICUAS.2017.7991446",
language = "English (US)",
series = "2017 International Conference on Unmanned Aircraft Systems, ICUAS 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "221--229",
booktitle = "2017 International Conference on Unmanned Aircraft Systems, ICUAS 2017",
address = "United States",
note = "2017 International Conference on Unmanned Aircraft Systems, ICUAS 2017 ; Conference date: 13-06-2017 Through 16-06-2017",
}