A Global Fundamental Matrix Estimation Method of Planar Motion Based on Inlier Updating
A fundamental matrix estimation based on matching points is a critical problem in epipolar geometry. In this paper, a global fundamental matrix estimation method based on inlier updating is proposed. Firstly, the coplanar constraint was incorporated into the solution of the fundamental matrix to red...
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MDPI AG
2022-06-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/12/4624 |
| _version_ | 1827656593682989056 |
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| author | Liang Wei Ju Huo |
| author_facet | Liang Wei Ju Huo |
| author_sort | Liang Wei |
| collection | DOAJ |
| description | A fundamental matrix estimation based on matching points is a critical problem in epipolar geometry. In this paper, a global fundamental matrix estimation method based on inlier updating is proposed. Firstly, the coplanar constraint was incorporated into the solution of the fundamental matrix to reduce the number of parameters to be solved. Subsequently, an inlier updating matrix was introduced according to the threshold of the epipolar geometry distance to eliminate the potential outliers and obtain a reliable initial value of the fundamental matrix. On this basis, we employed a four-point iterative method to estimate the fundamental matrix and make it satisfy the rank constraint at the same time. Finally, the epipolar geometry in binocular vision was extended to triple-view, and the fundamental matrix obtained in the previous step was globally optimized by minimizing the coordinate deviation between the intersection point and feature point in each group of images. The experiments show that the proposed fundamental matrix estimation method is robust to noise and outliers. In the attitude measurement, the maximum static error was 0.104° and dynamic measurement error was superior to 0.273°, which improved the reconstruction accuracy of feature points. Indoor images were further used to test the method, and the mean rotation angle error was 0.362°. The results demonstrate that the estimation method proposed in this paper has a good practical application prospect in multi-view 3D reconstruction and visual localization. |
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| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T22:30:34Z |
| publishDate | 2022-06-01 |
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| spelling | doaj.art-0f3a9b20473e4b8cb1efff0aca73c8522023-11-23T18:56:23ZengMDPI AGSensors1424-82202022-06-012212462410.3390/s22124624A Global Fundamental Matrix Estimation Method of Planar Motion Based on Inlier UpdatingLiang Wei0Ju Huo1School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, ChinaSchool of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, ChinaA fundamental matrix estimation based on matching points is a critical problem in epipolar geometry. In this paper, a global fundamental matrix estimation method based on inlier updating is proposed. Firstly, the coplanar constraint was incorporated into the solution of the fundamental matrix to reduce the number of parameters to be solved. Subsequently, an inlier updating matrix was introduced according to the threshold of the epipolar geometry distance to eliminate the potential outliers and obtain a reliable initial value of the fundamental matrix. On this basis, we employed a four-point iterative method to estimate the fundamental matrix and make it satisfy the rank constraint at the same time. Finally, the epipolar geometry in binocular vision was extended to triple-view, and the fundamental matrix obtained in the previous step was globally optimized by minimizing the coordinate deviation between the intersection point and feature point in each group of images. The experiments show that the proposed fundamental matrix estimation method is robust to noise and outliers. In the attitude measurement, the maximum static error was 0.104° and dynamic measurement error was superior to 0.273°, which improved the reconstruction accuracy of feature points. Indoor images were further used to test the method, and the mean rotation angle error was 0.362°. The results demonstrate that the estimation method proposed in this paper has a good practical application prospect in multi-view 3D reconstruction and visual localization.https://www.mdpi.com/1424-8220/22/12/4624planar motioninlier updatingtriple-view constraintglobal fundamental matrix3D reconstructionvisual localization |
| spellingShingle | Liang Wei Ju Huo A Global Fundamental Matrix Estimation Method of Planar Motion Based on Inlier Updating Sensors planar motion inlier updating triple-view constraint global fundamental matrix 3D reconstruction visual localization |
| title | A Global Fundamental Matrix Estimation Method of Planar Motion Based on Inlier Updating |
| title_full | A Global Fundamental Matrix Estimation Method of Planar Motion Based on Inlier Updating |
| title_fullStr | A Global Fundamental Matrix Estimation Method of Planar Motion Based on Inlier Updating |
| title_full_unstemmed | A Global Fundamental Matrix Estimation Method of Planar Motion Based on Inlier Updating |
| title_short | A Global Fundamental Matrix Estimation Method of Planar Motion Based on Inlier Updating |
| title_sort | global fundamental matrix estimation method of planar motion based on inlier updating |
| topic | planar motion inlier updating triple-view constraint global fundamental matrix 3D reconstruction visual localization |
| url | https://www.mdpi.com/1424-8220/22/12/4624 |
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