2D Visual odometry based on Probability Data Association Filter

DOI

10.2991/icecee-15.2015.138How to use a DOI?

Keywords

visual odometry;probability data association (PDA) filtering

Abstract

This paper presents a novel approach based on probability data association (PDA) filtering for estimating a vehicle’s trajectory in complex urban environments. We consider feature pairs acquired from consecutive frames as the measurements for the PDA filter to update the ego-motion vector of the camera. Compared to other feature based approaches, our approach presents a recursive filtering algorithm that provides dynamic estimation of ego-motion vector in the presence of falsely feature pairs. Experimental results show that this method provides good robustness under real traffic scenarios.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Bo Li
AU  - Shasha Dong
AU  - Liang Zhang
AU  - Yinhua Xu
PY  - 2015/06
DA  - 2015/06
TI  - 2D Visual odometry based on Probability Data Association Filter
BT  - Proceedings of the 2015 International Conference on Electrical, Computer Engineering and Electronics
PB  - Atlantis Press
SP  - 698
EP  - 702
SN  - 2352-538X
UR  - https://doi.org/10.2991/icecee-15.2015.138
DO  - 10.2991/icecee-15.2015.138
ID  - Li2015/06
ER  -