基于正交轮廓的全局最优姿态估计
Globally Optimal Pose from Orthographic Silhouettes
把轮廓面积随旋转轨迹的连续性转化为旋转空间上的强分支结构，配合预计算的轮廓签名响应面做分辨率引导的候选搜索，为无对应点的 3D 形状位姿估计提供可复用的全局最优求解框架。
原文依据 its continuity w.r.t trajectories in the rotation space
摘要译文
由模型翻译 · 术语统一 · 请对照原文核对关键结论本文解决从无遮挡轮廓确定 R^3 中已知形状姿态的问题。利用轮廓面积一个简单却鲜被探索的性质——它相对于旋转空间中轨迹的连续性——可以在全局最优意义下确定姿态。所提方法使用预计算的轮廓签名，将其建模为轮廓面积构成的响应面。在该轮廓签名响应面上进行查询以估计姿态，会在旋转搜索空间中产生强分支，从而使分辨率引导的候选搜索变得可行。此外，我们利用拟合到投影轮廓的二维椭圆的纵横比作为辅助的全局形状签名，以加速姿态搜索。这一组合策略构成了首个仅凭轮廓、无需对应点引导、对任意形状（无论其凸性与亏格如何）都能高效估计全局最优姿态的方法。我们在合成与真实样例上验证了该方法，相比同类方法取得了显著更高的精度。
英文原文摘要 1098 字符
We solve the problem of determining the pose of known shapes in \mathbb R ^3 from their unoccluded silhouettes. The pose is determined up to global optimality using a simple yet under-explored property of the area-of-silhouette: its continuity w.r.t trajectories in the rotation space. The proposed method utilises pre-computed silhouette-signatures, modelled as a response surface of the area-of-silhouettes. Querying this silhouette-signature response surface for pose estimation leads to a strong branching of the rotation search space, making resolution-guided candidate search feasible. Additionally, we utilise the aspect ratio of 2D ellipses fitted to projected silhouettes as an auxiliary global shape signature to accelerate the pose search. This combined strategy forms the first method to efficiently estimate globally optimal pose from just the silhouettes, without being guided by correspondences, for any shape, irrespective of its convexity and genus. We validate our method on synthetic and real examples, demonstrating significantly improved accuracy against comparable approaches.