Full Text:
<3339>
CLC number: TP391.4
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 0000-00-00
Cited: 1
Clicked: 5409
Visual odometry for road vehicles—feasibility analysis
| |||||||||||||
SOTELO Miguel-angel, GARCÍA Roberto, PARRA Ignacio, FERNÁNDEZ David, GAVILÁN Miguel, ÁLVAREZ Sergio, NARANJO José-eugenio. Visual odometry for road vehicles—feasibility analysis[J]. Journal of Zhejiang University Science A, 2007, 8(12): 2017-2020.
@article{title="Visual odometry for road vehicles—feasibility analysis",
author="SOTELO Miguel-angel, GARCÍA Roberto, PARRA Ignacio, FERNÁNDEZ David, GAVILÁN Miguel, ÁLVAREZ Sergio, NARANJO José-eugenio",
journal="Journal of Zhejiang University Science A",
volume="8",
number="12",
pages="2017-2020",
year="2007",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2007.A2017"
}
%0 Journal Article
%T Visual odometry for road vehicles—feasibility analysis
%A SOTELO Miguel-angel
%A GARCÍ
%A A Roberto
%A PARRA Ignacio
%A FERNÁ
%A NDEZ David
%A GAVILÁ
%A N Miguel
%A Á
%A LVAREZ Sergio
%A NARANJO José
%A -eugenio
%J Journal of Zhejiang University SCIENCE A
%V 8
%N 12
%P 2017-2020
%@ 1673-565X
%D 2007
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2007.A2017
TY - JOUR
T1 - Visual odometry for road vehicles—feasibility analysis
A1 - SOTELO Miguel-angel
A1 - GARCÍ
A1 - A Roberto
A1 - PARRA Ignacio
A1 - FERNÁ
A1 - NDEZ David
A1 - GAVILÁ
A1 - N Miguel
A1 - Á
A1 - LVAREZ Sergio
A1 - NARANJO José
A1 - -eugenio
J0 - Journal of Zhejiang University Science A
VL - 8
IS - 12
SP - 2017
EP - 2020
%@ 1673-565X
Y1 - 2007
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2007.A2017
Abstract: Estimating the global position of a road vehicle without using GPS is a challenge that many scientists look forward to solving in the near future. Normally, inertial and odometry sensors are used to complement GPS measures in an attempt to provide a means for maintaining vehicle odometry during GPS outage. Nonetheless, recent experiments have demonstrated that computer vision can also be used as a valuable source to provide what can be denoted as visual odometry. For this purpose, vehicle motion can be estimated using a non-linear, photogrametric approach based on RAndom SAmple Consensus (RANSAC). The results prove that the detection and selection of relevant feature points is a crucial factor in the global performance of the visual odometry algorithm. The key issues for further improvement are discussed in this letter.
[1] Agrawal, M., Konolige, K., 2006. Real-time Localization in Outdoor Environments Using Stereo Vision and Inexpensive GPS. 18th Int. Conf. on Pattern Recognition, p.1063-1068.
[2] Alonso, I.P., Llorca, D.F., Sotelo, M.A., Bergasa, L.M., de Toro, P.R., Nuevo, J., Ocana, M., Garrido, M.A.G., 2007. Combination of feature extraction methods for SVM pedestrian detection. IEEE Trans. on Intell. Transport. Syst., 8(2):292-307.
[3] Fischler, M.A., Bolles, R.C., 1981. Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM, 24(6):381-395.
[4] García, R., Sotelo, M., Parra, I., Fernández, D., Gavilán, M., Álvarez, S., Naranjo, J.E., 2007. Visual odometry for road vehicles. J. Intell. Rob. Syst., in press.
[5] Hagnelius, A., 2005. Visual Odometry. Master Thesis, Umea University.
[6] Nister, D., Naroditsky, O., Beren, J., 2004. Visual Odometry. Proc. IEEE Conf. on Computer Vision and Pattern Recognition, 1:652-659.
[7] Schmid, C., Mohr, R., Bauckhage, C., 2000. Evaluation of interest point detectors. Int. J. Computer Vision, 37(2):151-172.
Open peer comments: Debate/Discuss/Question/Opinion
<1>