Abstract
A set of multi-view panoramas may consist of various types of panoramic images in cylindrical representation, such as single-center, multi-center, concentric, symmetric, or (after a transformation onto a cylinder) catadioptric panoramas. In comparison with single-center imaging models, there are fewer studies on multiple view geometry for the multi-center cases. A generalized epipolar curve equation has been derived in a book publication in 2008. This article extends such result and presents a cost function whose minimization solves the camera pose estimation problem. Due to the non-linearity of the multi-centered projection geometry, the modeling of sensor pose estimation typically results into non-linear and highly complicated forms which incur numerical instability. This article focuses on evaluating a method for solving the pose estimation problem under a minor geometrical constraint, namely leveled panoramas. Extensive synthetic and real experiments along with a formal sensitivity analysis are carried out to demonstrate the robustness of the proposed method.
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