Papers › Robust Single Rotation Averaging
Robust Single Rotation Averaging
Seong Hun Lee, Javier Civera
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 L₂-mean. Second, we propose an outlier rejection scheme that can be incorporated in the Weiszfeld algorithm to improve the robustness of L₁ rotation averaging. Third, we propose a method for approximating the chordal L₁-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.
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