论文标题
部分可观测时空混沌系统的无模型预测
Robust Single Rotation Averaging
论文作者
论文摘要
我们提出了一种使用Weiszfeld算法平均单旋的新方法。我们的贡献是三重的：首先，我们根据输入旋转矩阵的元素中位数提出了一个可靠的初始化。我们的初始解决方案比常用的和弦$ l_2 $ -mean更准确，更健壮。其次，我们提出了一个异常拒绝方案，可以将其纳入Weiszfeld算法中，以提高$ L_1 $旋转平均的稳健性。第三，我们提出了一种使用weiszfeld算法近似$ l_1 $ - 均值的方法。一项广泛的评估表明，我们的方法和最新技术的状态与拟议的离群拒绝方案同样出色，但我们的拒绝方案的价格较快2-4美元。
We propose a novel method for single rotation averaging using the Weiszfeld algorithm. Our contribution is threefold: First, we propose a robust initialization based on the elementwise median of the input rotation matrices. Our initial solution is more accurate and robust than the commonly used chordal $L_2$-mean. Second, we propose an outlier rejection scheme that can be incorporated in the Weiszfeld algorithm to improve the robustness of $L_1$ rotation averaging. Third, we propose a method for approximating the chordal $L_1$-mean using the Weiszfeld algorithm. An extensive evaluation shows that both our method and the state of the art perform equally well with the proposed outlier rejection scheme, but ours is $2-4$ times faster.
