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Camera Pose Estimation Based on Quaternion from Least Feature Points |
1. School of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China
2. Qinhuangdao Institute of Audiovisual Machinery, Qinhuangdao, Hebei 066004, China |
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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.
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Received: 22 April 2019
Published: 14 May 2020
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