Abstract
We propose a novel approach to solve the problem of relative camera motion estimation with the information of known vertical direction in unstructured environments using the technique of 2D structure from motion (SFM). The information of vertical direction (gravity direction) can transform cameras into the camera of which vertical axis is parallel with the vertical direction. Moreover, feature point measurements can also be transformed into bearing angles and vertical coordinates with respect to this cameras. Then, 2D pose of the camera and 2D positions of point features can be estimated with 2D trifocal tensor method in closed form. After obtaining those estimates, the remained 1D information about camera and point features are estimated easily. The results of the experiments with simulated and real images are presented to demonstrate the feasibility of the proposed method. We also give the comparison between the proposed method and the state-of-the art method.
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Acknowledgments
This work was supported by ICT R&D program of MSIP/IITP. [R0126-15-1025, Development of 3D printing content creation/authoring/printing technology and its applications in the mobile environment].
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Kim, JH., Choi, J.S. (2016). Camera Motion Estimation with Known Vertical Direction in Unstructured Environments. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2016. Lecture Notes in Computer Science(), vol 10072. Springer, Cham. https://doi.org/10.1007/978-3-319-50835-1_15
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DOI: https://doi.org/10.1007/978-3-319-50835-1_15
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