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Modeling deformable human hands from medical images
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Symposium on Computer Animation archive
Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation table of contents
Grenoble, France
SESSION: Reality-based animation table of contents
Pages: 355 - 363  
Year of Publication: 2004
ISBN ~ ISSN:1727-5288 , 3-905673-14-2
Authors
Tsuneya Kurihara  Central Research Laboratory, Hitachi, Ltd., Tokyo, Japan
Natsuki Miyata  National Institute of Advanced Industrial Science and Technology, Tokyo, Japan
Sponsors
SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
Eurographics: Eurographics Association
Publisher
Eurographics Association  Aire-la-Ville, Switzerland, Switzerland
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Downloads (6 Weeks): 12,   Downloads (12 Months): 125,   Citation Count: 13
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ABSTRACT

This paper presents a new method for constructing an example-based deformable human hand model from medical images. Realistic animation of human hands requires good estimates of the joint structure and properly weighted skeleton-driven surface deformation. For this purpose, we propose a method based on medical images of hands in several poses. Our method consists of the following 3 steps: First, using the measured bone shapes, we estimate the link structure (joint rotation centers) and the joint angles of each scan. Second, we construct a mutually consistent polygonal mesh of all the scans. For this purpose, a polygonal mesh of one pose, the base mesh, is deformed using skeletal subspace deformation, and then fitted interactively to the measured meshes from the other scans. Finally, the hand is deformed using a weighted pose space deformation. We demonstrate results of deformable hand models consisting of 100,000 triangle meshes derived from CT scans.


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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{LGLM99} Larsen E., Gottschalk S., Lin M. C., Manocha D.: Fast Proximity Queries with Swept Sphere Volumes. Tech. Rep. TR99-018, Department of Computer Science, University of N. Carolina, Chapel Hill, 1999.
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{OBBH00} O'Brien J., Bodenheimer R., Brostow G., Hodgins J.: Automatic joint parameter estimation from magnetic motion capture data. In Graphics Interface (2000), pp. 53--60.
 
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{YCC99} Yasumuro Y., Chen Q., Chihara K.: Three-dimensional modeling of the human hand with motion constraints. Image and Vision Computing 17, 2 (1999), 149--156.

CITED BY  13

Collaborative Colleagues:
Tsuneya Kurihara: colleagues
Natsuki Miyata: colleagues