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

arXiv: https://arxiv.org/abs/1907.00534 · HTML: https://mlsanity.com/paper/1907.00534/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Jul 2019.

## Built on by (most cited first, 4 of 4)

- [Human Pose Estimation in Monocular Omnidirectional Top-View Images](https://mlsanity.com/paper/2304.08186/) (2023)
- [Applications of Deep Learning for Top-View Omnidirectional Imaging: A Survey](https://mlsanity.com/paper/2304.08193/) (2023)
- [NToP: NeRF-Powered Large-scale Dataset Generation for 2D and 3D Human Pose Estimation in Top-View Fisheye Images](https://mlsanity.com/paper/2402.18196/) (2024)
- [Towards Adaptive Fusion of Multimodal Deep Networks for Human Action Recognition](https://mlsanity.com/paper/2512.04943/) (2025)

## Abstract (arXiv)

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.