Human pose tracking in low dimensional space enhanced by limb correction

This paper proposes a two-level 3D human pose tracking method for a specific action captured by several cameras. The generation of pose estimates relies on fitting a 3D articulated model on a Visual Hull generated from the input images. First, an initial pose estimate is constrained by a low dimensi...

Full description

Saved in:
Bibliographic Details
Main Authors: Moutzouris, A., Martinez-del-Rincon, J., Lewandowski, M., Nebel, J., Makris, D.
Format: Conference Proceeding
Language:English
Subjects:
3D Pose Tracking
Computational modeling
Dimensionality Reduction
Humans
Manifolds
Particle filters
Solid modeling
Temporal Laplacian Eigenmaps
Three dimensional displays
Visual Hull
Visualization
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper proposes a two-level 3D human pose tracking method for a specific action captured by several cameras. The generation of pose estimates relies on fitting a 3D articulated model on a Visual Hull generated from the input images. First, an initial pose estimate is constrained by a low dimensional manifold learnt by Temporal Laplacian Eigenmaps. Then, an improved global pose is calculated by refining individual limb poses. The validation of our method uses a public standard dataset and demonstrates its accurate and computational efficiency.
ISSN:1522-4880
2381-8549
DOI:10.1109/ICIP.2011.6116100