Automatic Calibration of the Fisheye Camera for Egocentric 3D Human Pose Estimation from a Single Image
| Authors | |
|---|---|
| Publication date | 2021 |
| Book title | 2021 IEEE Winter Conference on Applications of Computer Vision |
| Book subtitle | proceedings : 5-9 January 2021, virtual event |
| ISBN |
|
| ISBN (electronic) |
|
| Series | WACV |
| Event | 2021 IEEE Winter Conference on Applications of Computer Vision |
| Pages (from-to) | 1771-1780 |
| Publisher | Los Alamitos, California: IEEE Computer Society |
| Organisations |
|
| Abstract |
We propose a method for egocentric 3D human pose estimation from a single image captured by a fisheye camera. The problem of estimating the egocentric 3D pose for a fisheye camera is that images may be subject to strong image distortions (e.g. 2D poses on the image plane that pass through the line of sight of the fisheye lens).Therefore, in this paper, we approach this problem by an automatic calibration module. Given a single image, our network first estimates 3D joint locations of a human in camera coordinates. To alleviate the impact of image distortions on 3D human pose estimation, we then use the automatic calibration to further regularize the 3D predictions. Experimental results demonstrate that the proposed method achieves state-of-the-art performance.
|
| Document type | Conference contribution |
| Language | English |
| Published at | https://doi.org/10.1109/WACV48630.2021.00181 |
| Other links | https://www.proceedings.com/58978.html |
| Permalink to this page | |