Name
Abstract | ||
|---|---|---|
A Kinect-based pose estimation system is presented for the study of movement problems within a rehab context. The performance of the system is compared to ground-truth data obtained by an expensive MoCap system. The results show that the proposed system performs well and could be used within a virtual rehabilitation context synchronized with other systems (e.g., robots). |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/CRV.2017.30 | 2017 14th Conference on Computer and Robot Vision (CRV) |
Keywords | Field | DocType |
human pose estimation,3D tracking,robotics,virtual reality,rehabilitation,Kinect V2 | Computer vision,Rehabilitation,Virtual reality,Computer science,Pose,Artificial intelligence,3d tracking,Robot,Robotics,Virtual rehabilitation | Conference |
ISBN | Citations | PageRank |
978-1-5386-2819-5 | 0 | 0.34 |
References | Authors | |
11 | 9 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael Bonenfant | 1 | 0 | 0.34 |
| Denis Laurendeau | 2 | 803 | 169.72 |
| Alexis Fortin-Cote | 3 | 1 | 1.70 |
| Philippe Cardou | 4 | 17 | 4.62 |
| Clément Gosselin | 5 | 484 | 66.28 |
| Celine Faure | 6 | 0 | 0.34 |
| Bradford J McFadyen | 7 | 28 | 3.94 |
| Catherine Mercier | 8 | 8 | 2.68 |
| Laurent Bouyer | 9 | 4 | 3.50 |