Abstract
Collinearity condition is generally used to establish relations between 3D objects and image points and calculate the absolute orientation parameters of image pairs in photogrammetry research. Given that the collinearity condition is a nonlinear system, the appropriate initial values of unknown absolute orientation parameters must be first established in the iterative least-squares solution. This research considers the coplanarity condition to solve relative orientation parameters as initial values and to solve absolute orientation parameters from the collinearity condition. The proposed method can provide a strategy for the motion estimation of a single camera. First, the algorithm automatically acquires conjugate image points between sequential images. Information on conjugate image points can provide information that can be used to solve relative orientation parameters from the coplanarity condition. Second, the absolute orientation parameters of a camera can be solved through the iterative least-squares method with the aid of ground control points. In addition to the absolute orientation parameters of a camera, the object coordinates of conjugate image points can be acquired. Finally, the camera trajectory can be obtained by repeating the procedure. This research conducted experiments in indoor and outdoor environments, and the results show that the proposed procedure is effective and feasible.
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Sih, YR., Chu, HJ., Tseng, YH. (2015). Ego-Motion Estimation by Using the Integration of Coplanarity and Collinearity Conditions. In: Gervasi, O., et al. Computational Science and Its Applications -- ICCSA 2015. ICCSA 2015. Lecture Notes in Computer Science(), vol 9156. Springer, Cham. https://doi.org/10.1007/978-3-319-21407-8_7
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DOI: https://doi.org/10.1007/978-3-319-21407-8_7
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