基于四元数最少特征点的相机位姿估计

doi:10.3969/j.issn.1000-1158.2020.05.07

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Abstract In order to solve the problem of camera pose estimation, a algorithm based on quaternion from least feature points was proposed. A polynomial system, established by constraints and feature points which were detected and matched in the two-dimensional image, was solved by corresponding matrix equation. Using quaternion to represent the rotation of the camera, which avoided the entanglement between rotation and translation in the process of solving. When the translation between two views is equal to zero, the problem can be solved well. The algorithm was deduced in detail by combining five-point algorithm and the anti-noise test was carried out. In the test, as the number of matched feature points increases, the average estimated error range of the algorithm does not exceed 2%. The KITTI dataset was used to test the usefulness of the algorithm and compare the results with several other methods. The results showed that under the same conditions, the algorithm improves the estimation accuracy by more than 24.5%, which shows a good estimation accuracy.

Key words： metrology camera pose estimation quaternion five point algorithm computer vision

Received: 22 April 2019 Published: 14 May 2020

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TB96

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	Articles by authors
	HOU Pei-guo
	ZHAO Zi-jian
	SONG Tao

Cite this article:

HOU Pei-guo,ZHAO Zi-jian,SONG Tao. Camera Pose Estimation Based on Quaternion from Least Feature Points[J]. Acta Metrologica Sinica, 2020, 41(5): 551-557.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2020.05.07 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2020/V41/I5/551

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