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Creating real body model of dressed human based on fat extent of body

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Abstract

The paper presents a method to estimate real body shape of dressed human. In the method we build a function to describe the fat extent of every vertex on the body. The fat extent is relative to the slim body template and the fat body template. Using the fat function and two templates a synthesizing model is created. The 3D scans of dressed human obtained by kinects are used to calculate the fat extents of feature rings on the bodies, and the results are used as the control points to build the fat function. We construct two databases corresponding to the persons wearing winter clothes and summer clothes respectively. The two databases consist of the fat extents of the feature rings on the naked bodies and on the 3D scans of dressed human. According the current season and the corresponding database, considering the proportional relations about these feature rings’ fat extents as restrictions, the real body of dressed human can be estimated with quadratic programming. The experiments demonstrate the availability of our method.

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References

  1. Alexa M (2003) Differential coordinates for local mesh morphing and deformation. Vis Comput 19(2–3):105–114

    MATH  Google Scholar 

  2. Allen B, Curless B, Popovic Z (2003) The space of human body shapes: reconstruction and parameterization from range scans. ACM Trans Graph 22(3):587–594

    Article  Google Scholar 

  3. Anguelov D, Srinivasan P, Koller D, Thrun S, Rodgers J (2005) SCAPE: Shape Completion and Animation of People. In ACM SIGGRAPH 2005 Papers, SIGGRAPH ‘05, pages 408–416, New York, NY, USA

  4. Balan AO, Black MJ (2008) The naked truth: Estimating Body Shape under Clothing. ECCV, pp. 15–29

  5. Balan A, Sigal L, Black MJ, Davis J, Haussecker H (2007) Detailed human shape and pose from images. CVPR, pp 1–8

  6. Chang W, Zwicker M (2011) Global registration of dynamic range scans for articulated model reconstruction. ACM Transactions on Graphics, 30:26:1–26:15, May

    Google Scholar 

  7. Charpiat G, Faugeras O, Keriven R (2005) Approximations of shape metrics and application to shape warping and empirical shape statistics. Found Comput Math 5(1):1–58

    Article  MATH  MathSciNet  Google Scholar 

  8. Cui Y, Stricker D (2011) 3D Shape Scanning with a Kinect. In ACM SIGGRAPH 2011 Posters, pages 57:1–57:1, New York, NY, USA

  9. Furakawa T, Gu J, Lee W-S, Magnenat-Thalmann N (2000) 3D clothes modeling from photo cloned human body. Proc., Virtual Worlds’2000, Paris, France, pp. 159–170

  10. Guan P, Weiss A, Balan AO, Black MJ (2009) Estimating human shape and pose from a single image. ICCV, pp. 1381–1388

  11. Hasler N, Ackermann H, Rosenhahn B, Thormahlen T, Seidel H-P (2010) Multilinear pose and body shape estimation of dressed subjects from image sets. CVPR, pp. 1823–1830

  12. Hasler N, Rosenhahn B, Seidel H-P (2007) Reverse engineering garments. In: Gagalowicz A, Philips W (eds) Migrage. Springer, Rocquencourt, pp 200–211

    Google Scholar 

  13. Hasler N, Stoll C, Rosenhahn B, Thormahlen T, Seidel H-P (2009) Estimating body shape of dressed humans. Comput Graph 33(3):211–216

    Article  Google Scholar 

  14. Hasler N, Stoll C, Sunkel M, Rosenhahn B, Seidel H-P (2009) A statistical model of human pose and body shape. Comput Graph Forum 28(2):337–346

    Article  Google Scholar 

  15. Magnenat-Thalmann N, Lyard E, Kasap M, Volino P (2008) Adaptive body, motion and cloth. In Motion in Games, volume5277 of Lecture Notes in Computer Science, pages 63–71. Springer Berlin/Heidelberg

  16. Magnenat-Thalmann N, Seo H, Cordier F (2004) Automatic modeling of virtual humans and body clothing. J Comput Sci Technol Chin Acad Sci 19(5):575–584

    Article  Google Scholar 

  17. Miao L, Qing Z, Huamin W, Yang R, Gong M (2009) Modeling deformable objects from a single depth camera. In IEEE 12th International Conference on Computer Vision, pages 167–174

  18. Seo H, Cordier F, Magnenat-Thalmann N (2003) Synthesizing animatable body models with parameterized. Eurographics/SIGGRAPH Symp Comput Animat 2003:120–125

    Google Scholar 

  19. Tong J, Zhou J, Liu L, Pan Z, Yan H (2012) Scanning 3D full human bodies using kinects. IEEE Trans Vis Comput Graph 18(4):643–650

    Article  Google Scholar 

  20. Weiss A, Hirshberg D, Black MJ (2011) Home 3D body scans from noisy image and range data. In 13th International Conference on Computer Vision, 1951–1958

  21. Zhou S, Fu H, Liu L, Cohen-Or D, Han X (2010) Parametric reshaping of human bodies in images. ACM Transactions on Graphics, 29(4), Article No. 126: 1–10

    Google Scholar 

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Acknowledgements

The authors acknowledge the supports from NSFC (Grant No. 61173124 and 61170318), key project of NSFC (Grant No. 61332017) and the national project (Grant No. 2013BAH24F00).

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Correspondence to Li Jun.

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Jun, L., Mingmin, Z., Zhigeng, P. et al. Creating real body model of dressed human based on fat extent of body. Multimed Tools Appl 74, 6951–6966 (2015). https://doi.org/10.1007/s11042-014-1947-9

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  • DOI: https://doi.org/10.1007/s11042-014-1947-9

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