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2011 18th IEEE International Conference on Image Processing

DOI: 10.1109/icip.2011.6116100

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Human pose tracking in low dimensional space enhanced by limb correction

Proceedings article published in 2011 by Alexandros Moutzouris, Jesús Martínez del Rincón, Jesus Martinez-Del-Rincon ORCID, Michal Lewandowski, Jean-Christophe Nebel, Dimitrios Makris
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This paper is available in a repository.

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Abstract

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.