English

Large Area 3D Human Pose Detection Via Stereo Reconstruction in Panoramic Cameras

Computer Vision and Pattern Recognition 2019-07-02 v1

Abstract

We propose a novel 3D human pose detector using two panoramic cameras. We show that transforming fisheye perspectives to rectilinear views allows a direct application of two-dimensional deep-learning pose estimation methods, without the explicit need for a costly re-training step to compensate for fisheye image distortions. By utilizing panoramic cameras, our method is capable of accurately estimating human poses over a large field of view. This renders our method suitable for ergonomic analyses and other pose based assessments.

Keywords

Cite

@article{arxiv.1907.00534,
  title  = {Large Area 3D Human Pose Detection Via Stereo Reconstruction in Panoramic Cameras},
  author = {Christoph Heindl and Thomas Pönitz and Andreas Pichler and Josef Scharinger},
  journal= {arXiv preprint arXiv:1907.00534},
  year   = {2019}
}
R2 v1 2026-06-23T10:08:11.599Z