基于视觉球面透视模型的消失点位姿计算方法
Calculating Pose with Vanishing Points of Visual-Sphere Perspective Model
AI总结：
提出一种基于视觉球面透视模型和消失点的几何算法，无需估计即可直接计算已知矩形目标的位姿矩阵，适用于超过180°视场的极端成像，支持嵌入式系统实现，具有高精度和低延迟特性。
摘要：
所提出方法的目标是直接获取已知矩形目标的位姿矩阵，无需估计，采用几何技术实现。该方法专为实时、超过180°视场角的极端成像设置（如鱼眼相机视图）而设计。所引入的算法利用几何代数来确定一对共面平行线（理想情况下为矩形中的切线对）的位姿。这是通过计算视觉单位球上的消失点来实现的，这些消失点对应于位姿矩阵向量。由于采用了视觉球面透视模型对视图坐标进行映射，该算法无需预先校正即可确定极端畸变视图源的位姿。映射可通过透视查找表或参数化通用透视畸变模型执行，后者也在本文中提出。其结果是稳健的位姿矩阵计算，可在使用微控制器的嵌入式系统上执行，提供高精度和低延迟。该方法可进一步扩展到立方体目标设置，用于全面的相机标定。它也可能在需要低延迟和极端视角的其他应用中具有价值。
英文摘要：
The goal of the proposed method is to directly obtain a pose matrix of a known rectangular target, without estimation, using geometric techniques. This method is specifically tailored for real-time, extreme imaging setups exceeding 180° field of view, such as a fish-eye camera view. The introduced algorithm employs geometric algebra to determine the pose for a pair of coplanar parallel lines (ideally a tangent pair as in a rectangle). This is achieved by computing vanishing points on a visual unit sphere, which correspond to pose matrix vectors. The algorithm can determine pose for an extremely distorted view source without prior rectification, owing to a visual-sphere perspective model mapping of view coordinates. Mapping can be performed using either a perspective map lookup or a parametric universal perspective distortion model, which is also presented in this paper. The outcome is a robust pose matrix computation that can be executed on an embedded system using a microcontroller, offering high accuracy and low latency. This method can be further extended to a cubic target setup for comprehensive camera calibration. It may also prove valuable in other applications requiring low latency and extreme viewing angles.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
