Camera Motion Estimation with Known Vertical Direction in Unstructured Environments

Jae-Hean Kim, Jin Sung Choi

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.