Calculating Pose with Vanishing Points of Visual-Sphere Perspective Model
It addresses pose estimation for applications requiring low latency and extreme viewing angles, such as embedded systems, but is incremental as it builds on geometric techniques.
The paper tackles the problem of directly computing a pose matrix for known rectangular targets in real-time extreme imaging setups like fish-eye cameras, achieving high accuracy and low latency on embedded systems without prior rectification.
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.