Research on stereo vision odometry

Xiaoling Zhang; Baofeng Zhang; Xiuzhen Tian

doi:10.1117/12.871713

9 November 2010 Research on stereo vision odometry

Xiaoling Zhang, Baofeng Zhang, Xiuzhen Tian

Proceedings Volume 7850, Optoelectronic Imaging and Multimedia Technology; 78500O (2010) https://doi.org/10.1117/12.871713
Event: Photonics Asia 2010, 2010, Beijing, China

Abstract

The stereo visual odometer in vision based on the navigation system is proposed in the paper. The stereo visual odometer can obtain the motion data to implement the position and attitude estimation of ALV(Autonomous Land Vehicle). Two key technology in the stereo vision odometer are dissertated. The first is using SIFT(Scale Invariant Feature Transform) to extract suitable feature, match points pairs in the feature, and track the feature of fore and after frames of the same point on the object. The second is using matching and tracking to obtain the different 3-D coordinate of the feature of the point on the object, and to compute the motion parameters by motion estimate. The unknown outdoor environment is adopted in the experiment. The results show that the stereo vision odometer is more accurate, and the measurement error dose not increase with the movement distance increasing. It can be used as an important supplement of conventional odometer.

Citation Download Citation

Xiaoling Zhang, Baofeng Zhang, and Xiuzhen Tian "Research on stereo vision odometry", Proc. SPIE 7850, Optoelectronic Imaging and Multimedia Technology, 78500O (9 November 2010); https://doi.org/10.1117/12.871713

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available