  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.
