Human body shape and motion tracking by hierarchical weighted ICP

Jia Chen; Xiaojun Wu; Michael Yu Wang; Fuqin Deng

doi:10.1007/978-3-642-24031-7_41

Human body shape and motion tracking by hierarchical weighted ICP

Jia Chen^*, Xiaojun Wu, Michael Yu Wang, Fuqin Deng

^*Corresponding author for this work

Research output: Contribution to journal › Conference article published in journal › peer-review

6 Citations (Scopus)

Abstract

We present a new approach for tracking both the human body shape and the whole body motion with complete six DOF of each body limb without imposing rotation or translation constraints. First, a surface mesh with highly improved quality is obtained by using our new silhouette-based visual hull reconstruction method for each frame of multi-view videos. Then, a skinned mesh model is fitted to the data using hierarchical weighted ICP (HWICP) algorithm, where an easy-to-adjust strategy for selecting the set of ICP registration points is given based on the weights of the skinned model and the Approximate Nearest Neighbors (ANN) method is applied for fast searching nearest neighbors. By comparing HWICP with the general hierarchical ICP (Iterative Closest Point) method based on synthetic data, we demonstrate the power of weighting corresponding point pairs in HWICP, especially when adjacent body segments of target are near 'cylindrical-shaped'.

Original language	English
Pages (from-to)	408-417
Number of pages	10
Journal	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6939 LNCS
Issue number	PART 2
DOIs	https://doi.org/10.1007/978-3-642-24031-7_41
Publication status	Published - 2011
Externally published	Yes
Event	7th International Symposium on Visual Computing, ISVC 2011 - Las Vegas, NV, United States Duration: 26 Sept 2011 → 28 Sept 2011

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10.1007/978-3-642-24031-7_41

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title = "Human body shape and motion tracking by hierarchical weighted ICP",

abstract = "We present a new approach for tracking both the human body shape and the whole body motion with complete six DOF of each body limb without imposing rotation or translation constraints. First, a surface mesh with highly improved quality is obtained by using our new silhouette-based visual hull reconstruction method for each frame of multi-view videos. Then, a skinned mesh model is fitted to the data using hierarchical weighted ICP (HWICP) algorithm, where an easy-to-adjust strategy for selecting the set of ICP registration points is given based on the weights of the skinned model and the Approximate Nearest Neighbors (ANN) method is applied for fast searching nearest neighbors. By comparing HWICP with the general hierarchical ICP (Iterative Closest Point) method based on synthetic data, we demonstrate the power of weighting corresponding point pairs in HWICP, especially when adjacent body segments of target are near 'cylindrical-shaped'.",

author = "Jia Chen and Xiaojun Wu and Wang, \{Michael Yu\} and Fuqin Deng",

year = "2011",

doi = "10.1007/978-3-642-24031-7\_41",

language = "English",

volume = "6939 LNCS",

pages = "408--417",

journal = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

issn = "0302-9743",

publisher = "Springer Science and Business Media Deutschland GmbH",

number = "PART 2",

note = "7th International Symposium on Visual Computing, ISVC 2011 ; Conference date: 26-09-2011 Through 28-09-2011",

}

Human body shape and motion tracking by hierarchical weighted ICP. / Chen, Jia; Wu, Xiaojun; Wang, Michael Yu et al.
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 6939 LNCS, No. PART 2, 2011, p. 408-417.

Research output: Contribution to journal › Conference article published in journal › peer-review

TY - JOUR

T1 - Human body shape and motion tracking by hierarchical weighted ICP

AU - Chen, Jia

AU - Wu, Xiaojun

AU - Wang, Michael Yu

AU - Deng, Fuqin

PY - 2011

Y1 - 2011

N2 - We present a new approach for tracking both the human body shape and the whole body motion with complete six DOF of each body limb without imposing rotation or translation constraints. First, a surface mesh with highly improved quality is obtained by using our new silhouette-based visual hull reconstruction method for each frame of multi-view videos. Then, a skinned mesh model is fitted to the data using hierarchical weighted ICP (HWICP) algorithm, where an easy-to-adjust strategy for selecting the set of ICP registration points is given based on the weights of the skinned model and the Approximate Nearest Neighbors (ANN) method is applied for fast searching nearest neighbors. By comparing HWICP with the general hierarchical ICP (Iterative Closest Point) method based on synthetic data, we demonstrate the power of weighting corresponding point pairs in HWICP, especially when adjacent body segments of target are near 'cylindrical-shaped'.

AB - We present a new approach for tracking both the human body shape and the whole body motion with complete six DOF of each body limb without imposing rotation or translation constraints. First, a surface mesh with highly improved quality is obtained by using our new silhouette-based visual hull reconstruction method for each frame of multi-view videos. Then, a skinned mesh model is fitted to the data using hierarchical weighted ICP (HWICP) algorithm, where an easy-to-adjust strategy for selecting the set of ICP registration points is given based on the weights of the skinned model and the Approximate Nearest Neighbors (ANN) method is applied for fast searching nearest neighbors. By comparing HWICP with the general hierarchical ICP (Iterative Closest Point) method based on synthetic data, we demonstrate the power of weighting corresponding point pairs in HWICP, especially when adjacent body segments of target are near 'cylindrical-shaped'.

UR - https://www.scopus.com/pages/publications/80053354192

U2 - 10.1007/978-3-642-24031-7_41

DO - 10.1007/978-3-642-24031-7_41

M3 - Conference article published in journal

AN - SCOPUS:80053354192

SN - 0302-9743

VL - 6939 LNCS

SP - 408

EP - 417

JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

IS - PART 2

T2 - 7th International Symposium on Visual Computing, ISVC 2011

Y2 - 26 September 2011 through 28 September 2011

ER -

Human body shape and motion tracking by hierarchical weighted ICP

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