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CLC number: TP391.4

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Received: 2007-08-24

Revision Accepted: 2007-10-30

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Journal of Zhejiang University SCIENCE A 2007 Vol.8 No.12 P.2017-2020


Visual odometry for road vehicles—feasibility analysis

Author(s):  SOTELO Miguel-angel, GARCÍ,A Roberto, PARRA Ignacio, FERNÁ,NDEZ David, GAVILÁ,N Miguel, Á,LVAREZ Sergio, NARANJO José,-eugenio

Affiliation(s):  Department of Electronics, University of Alcalá more

Corresponding email(s):   sotelo@depeca.uah.es

Key Words:  3D visual odometry, Ego-motion estimation, RAndom SAmple Consensus (RANSAC), Photogrametric approach

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.

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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.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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[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.

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