Simplified mirror-based camera pose computation via rotation averaging
Simplified mirror-based camera pose computation via rotation averaging
复制标题
通过旋转平均简化基于镜子的相机姿态计算
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
Qifeng Yu
中科院分区：
文献类型：
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作者：
Gucan Long;L. Kneip;Xin Li;Xiaohu Zhang;Qifeng Yu
我们提出了一种新颖的方法来计算相机相对于仅给出镜像视图的参考对象的姿态。后者源自处于不同未知姿势的平面镜。这个问题在一些外部相机校准场景中高度相关，在这些场景中相机无法直接看到参考对象。与许多现有方法相比，我们的方法不采用固定轴旋转约束，而是代表了一种更优雅的公式作为旋转平均问题。我们的理论贡献将旋转平均的适用性扩展到更一般的情况，并能够在弦 L2 度量下以封闭形式进行基于镜像的姿态估计，或者通过采用迭代 L1 范数平均以异常值稳健的方式进行估计。我们展示了我们的方法在合成数据和真实数据上的优势，并展示了如何应用该方法来校准普通智能手机的非重叠摄像头对。
We propose a novel approach to compute the camera pose with respect to a reference object given only mirrored views. The latter originate from a planar mirror at different unknown poses. This problem is highly relevant in several extrinsic camera calibration scenarios, where the camera cannot see the reference object directly. In contrast to numerous existing methods, our approach does not employ the fixed axis rotation constraint, but represents a more elegant formulation as a rotation averaging problem. Our theoretical contribution extends the applicability of rotation averaging to a more general case, and enables mirror-based pose estimation in closed-form under the chordal L2-metric, or in an outlier-robust way by employing iterative L1-norm averaging. We demonstrate the advantages of our approach on both synthetic and real data, and show how the method can be applied to calibrate the non-overlapping pair of cameras of a common smart phone.