In this paper, we propose a novel solution for multi-view reconstruction, relative pose and homography estimation using planar regions. The proposed method doesn‘t require point matches, it directly uses a pair of planar image regions and simultaneously reconstructs the normal and distance of the corresponding 3D planar surface patch, the relative pose of the cameras as well as the aligning homography between the image regions. When more than two cameras are available, then a special region-based bundle adjustment is proposed, which provides robust estimates in a multi-view camera system by constructing and solving a non-linear system of equations. The method is quantitatively evaluated on a large synthetic dataset as well as on the KITTI vision benchmark dataset.
CITATION STYLE
Frohlich, R., & Kato, Z. (2019). Simultaneous Multi-view Relative Pose Estimation and 3D Reconstruction from Planar Regions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11367 LNCS, pp. 467–483). Springer Verlag. https://doi.org/10.1007/978-3-030-21074-8_37
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