Name
Title | ||
|---|---|---|
Human Pose Estimation by Exploiting Spatial and Temporal Constraints in Body-Part Configurations. |
Abstract | ||
|---|---|---|
We present an algorithm for estimating a sequence of articulated upper-body human pose in unconstrained videos. Most previous work often fails to locate forearms in those video scenes suffering from illumination varieties, background clutter, camera shake, or occlusion. In order to deal with such intractable cases, we propose a novel algorithm for addressing the problem of certain body parts local... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/ACCESS.2016.2643439 | IEEE Access |
Keywords | Field | DocType |
Pose estimation,Context,Videos,Biological system modeling,Context modeling,Computational modeling,Lighting | Computer vision,Degrees of freedom (statistics),Shake,Clutter,Computer science,3D pose estimation,Pose,Context model,Artificial intelligence,Temporal context,Articulated body pose estimation | Journal |
Volume | ISSN | Citations |
5 | 2169-3536 | 1 |
PageRank | References | Authors |
0.35 | 34 | 5 |