Details
Original language | English |
---|---|
Pages (from-to) | 400-409 |
Number of pages | 10 |
Journal | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Volume | 2124 |
Publication status | Published - 30 Aug 2001 |
Abstract
In this paper we propose a method for the automated acquisition of 3D human models for real-time animation. The individual to be modelled is placed in a monochrome environment and captured simultaneously by a set of 16 calibrated cameras distributed on a metal support above and around the head. A number of image sets is taken from various postures. A binary volume model will then be reconstructed from each image set via a shape-from-silhouette approach. Based on the surface shape and a reliable 3D skeletonisation of the volume model, a parametric human body template is _tted to each captured posture independently. Finally, from the parameter sets obtained initially, one unique set of posture-invariant parameters and the corresponding mul- tiple sets of posture-dependent parameters are estimated using iterative optimisation. The resulting model consists of a fully textured triangular surface mesh over a bone structure, ready to be used in real-time appli- cations such as 3D video-conferencing or o_-the-shelf multi-player games.
Keywords
- 3D videoconferenc-ing, Human models, Shape-from-silhouette
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
- General Computer Science
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In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 2124, 30.08.2001, p. 400-409.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Automated acquisition of lifelike 3D human models from multiple posture data
AU - Wingbermühle, Jochen
AU - Liedtke, Claus Eberhard
AU - Solodenko, Juri
PY - 2001/8/30
Y1 - 2001/8/30
N2 - In this paper we propose a method for the automated acquisition of 3D human models for real-time animation. The individual to be modelled is placed in a monochrome environment and captured simultaneously by a set of 16 calibrated cameras distributed on a metal support above and around the head. A number of image sets is taken from various postures. A binary volume model will then be reconstructed from each image set via a shape-from-silhouette approach. Based on the surface shape and a reliable 3D skeletonisation of the volume model, a parametric human body template is _tted to each captured posture independently. Finally, from the parameter sets obtained initially, one unique set of posture-invariant parameters and the corresponding mul- tiple sets of posture-dependent parameters are estimated using iterative optimisation. The resulting model consists of a fully textured triangular surface mesh over a bone structure, ready to be used in real-time appli- cations such as 3D video-conferencing or o_-the-shelf multi-player games.
AB - In this paper we propose a method for the automated acquisition of 3D human models for real-time animation. The individual to be modelled is placed in a monochrome environment and captured simultaneously by a set of 16 calibrated cameras distributed on a metal support above and around the head. A number of image sets is taken from various postures. A binary volume model will then be reconstructed from each image set via a shape-from-silhouette approach. Based on the surface shape and a reliable 3D skeletonisation of the volume model, a parametric human body template is _tted to each captured posture independently. Finally, from the parameter sets obtained initially, one unique set of posture-invariant parameters and the corresponding mul- tiple sets of posture-dependent parameters are estimated using iterative optimisation. The resulting model consists of a fully textured triangular surface mesh over a bone structure, ready to be used in real-time appli- cations such as 3D video-conferencing or o_-the-shelf multi-player games.
KW - 3D videoconferenc-ing
KW - Human models
KW - Shape-from-silhouette
UR - http://www.scopus.com/inward/record.url?scp=84947919616&partnerID=8YFLogxK
U2 - 10.1007/3-540-44692-3_49
DO - 10.1007/3-540-44692-3_49
M3 - Article
AN - SCOPUS:84947919616
VL - 2124
SP - 400
EP - 409
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)
SN - 0302-9743
ER -