Name
Abstract | ||
|---|---|---|
We address the task of estimating 3D human poses from monocular camera sequences. Many works make use of multiple consecutive frames for the estimation of a 3D pose in a frame. Although such an approach should ease the pose estimation task substantially since multiple consecutive frames allow to solve for 2D projection ambiguities in principle, it has not yet been investigated systematically how much we can improve the 3D pose estimates when using multiple consecutive frames opposed to single frame information.In this paper we analyze the difference in quality of 3D pose estimates based on different numbers of consecutive frames from which 2D pose estimates are available. We validate the use of temporal information on two major different approaches for human pose estimation - modeling and learning approaches. The results of our experiments show that both learning and modeling approaches benefit from using multiple frames opposed to single frame input but that the benefit is small when the 2D pose estimates show a high quality in terms of precision. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ICCVW.2011.6130348 | 2011 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCV WORKSHOPS) |
Keywords | Field | DocType |
3d pose estimation,vectors,image reconstruction,estimation,learning artificial intelligence,pose estimation,mathematical model,three dimensional | Iterative reconstruction,Computer vision,Pattern recognition,Computer science,Solid modelling,3D pose estimation,Pose,Monocular camera,Artificial intelligence,Articulated body pose estimation,Monocular | Conference |
Volume | Issue | Citations |
2011 | 1 | 1 |
PageRank | References | Authors |
0.36 | 12 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jürgen Brauer | 1 | 4 | 1.76 |
| Wenjuan Gong | 2 | 80 | 10.28 |
| Jordi Gonzalez | 3 | 617 | 48.02 |
| Michael Arens | 4 | 391 | 35.83 |