Relative pose estimation has become a fundamental and important problem in visual simultaneous localization and mapping. This paper statistically optimizes the solution for the homography-based relative pose estimation problem. Assuming a known gravity direction and a dominant ground plane, the homography representation in the normalized image plane enables a least squares pose estimation between two views. Furthermore, an iterative estimation method of the camera trajectory is developed for visual odometry. The accuracy and robustness of the proposed algorithm are experimentally tested on synthetic and real data in indoor and outdoor environments. Various metrics confirm the effectiveness of the proposed method in practical applications.

相对姿态估计已成为视觉同时定位和制图中的基本和重要问题。本文从统计角度优化了基于单应性的相对姿势估计问题的解决方案。假设已知重力方向和主要地平面，则归一化图像平面中的单应性表示法可实现两个视图之间的最小二乘姿势估计。此外，针对视觉测距法开发了相机轨迹的迭代估计方法。该算法的准确性和鲁棒性在室内和室外环境下对合成数据和真实数据进行了实验测试。各种指标证实了该方法在实际应用中的有效性。