Robust visual odometry based on front and back cameras

Computer Engineering & Science

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Robust visual odometry based on front and back cameras

SHI Xiao-tian1,ZHANG Yu2,FANG Zhou1

(1.College of Aeronautics and Astronautics,Zhejiang University,Hangzhou 310027;

2.College of Control Science and Engineering,Zhejiang University,Hangzhou 310027,China)

Received:2016-04-25 Revised:2016-07-01 Online:2017-10-25 Published:2017-10-25

Abstract

Abstract:

We propose a new visual odometry method to use front and back cameras at the same time due to the terrible

impact of luminance on indoor visual odometry and the dual-camera feature of modern mobile devices. By the

state estimation of the visual odometry on each side, we can achieve the sustained output even when one side

fails, and the robustness of visual odometry is improved. In addition, we fusion the output of the two-side

visual odometry by Kalman filter to improve the accuracy when the two sides both run normally. Experimental

results under various practical environments in various velocities show that the system can output regularly

even when one side fails and the accuracy of the output is improved when the two sides work normally.

Key words: visual odometry, Kalman filter, information fusion, smart phone

SHI Xiao-tian1,ZHANG Yu2,FANG Zhou1.

Robust visual odometry based on front and back cameras

[J]. Computer Engineering & Science.

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Robust visual odometry based on front and back cameras

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