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.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the OAGM Workshop 2018 -- Medical Image Analysis |
| Pages | 103-110 |
| Number of pages | 8 |
| Publication status | Published - May 2018 |
Fields of science
- 202002 Audiovisual media
- 102 Computer Sciences
- 102001 Artificial intelligence
- 102003 Image processing
- 102015 Information systems
JKU Focus areas
- Computation in Informatics and Mathematics
- Engineering and Natural Sciences (in general)