Human pose tracking in low dimensional space enhanced by limb correction

A. Moutzouris; J. Martinez-Del-Rincon; M. Lewandowski; J.-C. Nebel; D. Makris

doi:10.1109/ICIP.2011.6116100

Human pose tracking in low dimensional space enhanced by limb correction

A. Moutzouris
, J. Martinez-Del-Rincon
, M. Lewandowski
, J.-C. Nebel
, D. Makris

Research output: Chapter in Book/Report/Conference proceeding › Other chapter contribution

5 Citations (Scopus)

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.

Original language	English
Title of host publication	Proceedings - International Conference on Image Processing, ICIP
Place of Publication	NEW YORK
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2301-2304
Number of pages	4
ISBN (Print)	978-1-4577-1303-3
DOIs	https://doi.org/10.1109/ICIP.2011.6116100
Publication status	Published - 2011
Event	18th IEEE International Conference on Image Processing (ICIP) - Brussels, Belgium Duration: 11 Sept 2011 → 14 Sept 2011

Conference

Conference	18th IEEE International Conference on Image Processing (ICIP)
Country/Territory	Belgium
City	Brussels
Period	11/09/2011 → 14/09/2011

Access to Document

10.1109/ICIP.2011.6116100

Cite this

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title = "Human pose tracking in low dimensional space enhanced by limb correction",

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.",

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booktitle = "Proceedings - International Conference on Image Processing, ICIP",

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note = "18th IEEE International Conference on Image Processing (ICIP) ; Conference date: 11-09-2011 Through 14-09-2011",

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Moutzouris, A, Martinez-Del-Rincon, J, Lewandowski, M, Nebel, J-C & Makris, D 2011, Human pose tracking in low dimensional space enhanced by limb correction. in Proceedings - International Conference on Image Processing, ICIP. Institute of Electrical and Electronics Engineers Inc., NEW YORK, pp. 2301-2304, 18th IEEE International Conference on Image Processing (ICIP), Brussels, Belgium, 11/09/2011. https://doi.org/10.1109/ICIP.2011.6116100

Human pose tracking in low dimensional space enhanced by limb correction. / Moutzouris, A.; Martinez-Del-Rincon, J.; Lewandowski, M. et al.
Proceedings - International Conference on Image Processing, ICIP. NEW YORK: Institute of Electrical and Electronics Engineers Inc., 2011. p. 2301-2304.

Research output: Chapter in Book/Report/Conference proceeding › Other chapter contribution

TY - CHAP

T1 - Human pose tracking in low dimensional space enhanced by limb correction

AU - Moutzouris, A.

AU - Martinez-Del-Rincon, J.

AU - Lewandowski, M.

AU - Nebel, J.-C.

AU - Makris, D.

PY - 2011

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AB - 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.

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DO - 10.1109/ICIP.2011.6116100

M3 - Other chapter contribution

AN - SCOPUS:84856300585

SN - 978-1-4577-1303-3

SP - 2301

EP - 2304

BT - Proceedings - International Conference on Image Processing, ICIP

PB - Institute of Electrical and Electronics Engineers Inc.

CY - NEW YORK

T2 - 18th IEEE International Conference on Image Processing (ICIP)

Y2 - 11 September 2011 through 14 September 2011

ER -

Human pose tracking in low dimensional space enhanced by limb correction

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