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Proceedings Paper

Monocular visual odometry based on inverse perspective mapping
Author(s): Yu Cao; Ying Feng; Yun-tao Yang; Yun-jin Chen; Bing Lei; Li-shuang Zhao
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Paper Abstract

The monocular vision odometry simplifies the hardware and the software as opposed to the stereo vision odometry, but it also has defect. When the vehicle is in motion, the camera's attitude changes inevitably, what lead that the method's performance degrades. To solve this problem, we proposed a monocular visual odometry based on the inverse perspective mapping (IPM). Attitude of the camera is monitored in real time by the attitude sensor when the vehicle is moving. Then the images of road surface photographed by camera became top view by using the IPM algorithm, after that, the characters of images can be calculated by the Speeded Up Robust Features (SURF) algorithm. By the random sample consensus (RANSAC) algorithm, the amounts of translation and rotation between two adjacent images can be concluded. Accordingly, the movement distance and the course of the vehicle can be worked out. In order to test the ranging accuracy of the method, both static and dynamic experiments were implemented. Static experiment showed that the average accuracy of ranging of this method achieved 1.6%. Dynamic experiment showed that the ranging accuracy achieved 6%, and the heading measurement error is less than 1.3°. Therefore, the method proposed in this paper is easy to operate, time-efficient, low cost, and the accuracy of the method in ranging and heading measurement are demonstrated.

Paper Details

Date Published: 18 August 2011
PDF: 7 pages
Proc. SPIE 8194, International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, 819418 (18 August 2011); doi: 10.1117/12.900010
Show Author Affiliations
Yu Cao, National Univ. of Defense Technology (China)
Ying Feng, National Univ. of Defense Technology (China)
Yun-tao Yang, National Univ. of Defense Technology (China)
Yun-jin Chen, National Univ. of Defense Technology (China)
Bing Lei, National Univ. of Defense Technology (China)
Li-shuang Zhao, National Univ. of Defense Technology (China)


Published in SPIE Proceedings Vol. 8194:
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications
Makoto Ikeda; Nanjian Wu; Guangjun Zhang; Kecong Ai, Editor(s)

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