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Continuous capture of skin deformation
Full text MovMov (19:41),  PdfPdf (6.55 MB)
Source ACM Transactions on Graphics (TOG) archive
Volume 22 ,  Issue 3  (July 2003) table of contents
Proceedings of ACM SIGGRAPH 2003
SESSION: Human bodies table of contents
Pages: 578 - 586  
Year of Publication: 2003
ISSN:0730-0301
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Authors
Peter Sand  Massachusetts Institute of Technology
Leonard McMillan  University of North Carolina, Chapel Hill
Jovan Popović  Massachusetts Institute of Technology
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 12,   Downloads (12 Months): 114,   Citation Count: 20
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ABSTRACT

We describe a method for the acquisition of deformable human geometry from silhouettes. Our technique uses a commercial tracking system to determine the motion of the skeleton, then estimates geometry for each bone using constraints provided by the silhouettes from one or more cameras. These silhouettes do not give a complete characterization of the geometry for a particular point in time, but when the subject moves, many observations of the same local geometries allow the construction of a complete model. Our reconstruction algorithm provides a simple mechanism for solving the problems of view aggregation, occlusion handling, hole filling, noise removal, and deformation modeling. The resulting model is parameterized to synthesize geometry for new poses of the skeleton. We demonstrate this capability by rendering the geometry for motion sequences that were not included in the original datasets.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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BRAND, M. 2001. Morphable 3D models from video. In Proceedings of the IEEE conference on Computer Vision and Pattern Recognition (CVPR), II:456--463.
 
4
BREGLER, C., HERTZMANN, A., AND BIERMANN, H. 2000. Recovering non-rigid 3D shape from image streams. In Proceedings of the IEEE conference on Computer Vision and Pattern Recognition (CVPR), II:690--696.
 
5
BROOMHEAD, D., AND LOWE, D. 1988. Multivariable functional interpolation and adaptive networks. Complex Systems 2, 3, 321--355.
6
 
7
 
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GU, X., GORTLER, S. J., HOPPE, H., MCMILLAN, L., BROWN, B. J., AND STONE, A. D. 1999. Silhouette mapping. Tech. Rep. TR-1-99, Harvard.
9
 
10
 
11
KAYDARA. 2001. FiLMBOX Reference Guide. Kaydara Inc., Montréal, Québec.
 
12
 
13
 
14
 
15
NEBEL, J.-C., RODRIGUEZ-MIGUEL, F. J., AND COCKSHOTT, W. P. 2001. Stroboscopic stereo rangefinder. In Proceedings of the Third International Conference on 3D Imaging and Modeling, 59--64.
 
16
NELDER, J. A., AND MEAD, R. 1965. A simplex method for function minimization. Computer Journal 7, 4, 308--313.
 
17
NEVATIA, R., AND BINFORD, T. O. 1977. Description and recognition of curved objects. Artificial Intelligence 8, 1, 77--98.
 
18
PLÄNKERS, R., AND FUA, P. 2001. Articulated soft objects for video-based body modeling. In Proceedings of the 8th IEEE International Conference on Computer Vision (ICCV), I:394--401.
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20
 
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STOKDYK, S., HAHN, K., NOFZ, P., AND ANDERSON, G., 2002. Spiderman: Behind the mask. Special Session of SIGGRAPH 2002.
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23
 
24
 
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VICON. 2003. Vicon iQ Reference Manual. Vicon Motion Systems Inc., Lake Forest, CA.
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CITED BY  20

Collaborative Colleagues:
Peter Sand: colleagues
Leonard McMillan: colleagues
Jovan Popović: colleagues