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Estimating 3D human shapes from measurements

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Abstract

Recent advances in 3D imaging technologies give rise to databases of human shapes, from which statistical shape models can be built. These statistical models represent prior knowledge of the human shape and enable us to solve shape reconstruction problems from partial information. Generating human shape from traditional anthropometric measurements is such a problem, since these 1D measurements encode 3D shape information. Combined with a statistical shape model, these easy-to-obtain measurements can be leveraged to create 3D human shapes. However, existing methods limit the creation of the shapes to the space spanned by the database and thus require a large amount of training data. In this paper, we introduce a technique that extrapolates the statistically inferred shape to fit the measurement data using non-linear optimization. This method ensures that the generated shape is both human-like and satisfies the measurement conditions. We demonstrate the effectiveness of the method and compare it to existing approaches through extensive experiments, using both synthetic data and real human measurements.

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  1. http://www.sae.org/standardsdev/tsb/cooperative/caesumm.htm.

References

  1. Allen, B., Curless, B., Popović, Z.: Proceedings of SIGGRAPH. The space of human body shapes: reconstruction and parameterization from range scans. ACM transactions on graphics, 22(3):587–594, (2003)

  2. Allen, B., Curless, B., Popović, Z.: Exploring the space of human body shapes: data-driven synthesis under anthropometric control. In SAE symposium on digital human modeling for design and, engineering, paper \(\#\) 2188, (2004)

  3. Anguelov, D., Srinivasan, P., Koller, D., Thrun, S., Rodgers, J., Davis, J.: Proceedings of SIGGRAPH. Scape: shape completion and animation of people. ACM transactions on graphics, 24(3):408–416, (2005)

  4. Baek, S.-Y., Lee, K.: Parametric human body shape modeling framework for human-centered product design. Comput-Aided Des. 44(1), 56–67 (2012)

    Article  Google Scholar 

  5. Barber, C.B., Dobkin, D.P., Huhdanpaa, H.: The quickhull algorithm for convex hulls. ACM Trans. Math. Softw. 22(4), 469–483 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  6. Blanz, V., Vetter, T.: In Proceedings of SIGGRAPH, a morphable model for the synthesis of 3d faces. pp. 187–194 (1999)

  7. Boisvert, J., Shu, C., Wuhrer, S., Xi, P.: Three-dimensional human shape inference from silhouettes: reconstruction and validation. Mach Vision Appl, 2012

  8. Chen, Y., Cipolla, R.: Learning shape priors for single view reconstruction. In workshop on 3D imaging and modelling, pp. 1425–1432 (2009)

  9. Chu, C.-H., Tsai, Y.-T., Wang, C.C., Kwok, T.-H.: Exemplar-based statistical model for semantic parametric design of human body. Compt. Ind. 61(6), 541–549 (2010)

    Article  Google Scholar 

  10. DeCarlo, D., Metaxas, D., Stone, M.: In Proceedings of SIGGRAPH, an anthropometric face model using variational techniques. pp. 67–74 (1998)

  11. Dijkstra, E.W.: A note on two problems in connexion with graphs. Numerische Mathematik 1(1), 269–271 (1959)

    Article  MathSciNet  MATH  Google Scholar 

  12. Dryden, I., Mardia, K.: Statist. Shape Anal. Wiley, Chichester (2002)

    Google Scholar 

  13. Ek, C.H., Torr, P.H.S., Lawrence, N.D.: In Workshop on Machine Learning for Multimodal, Interaction. Gaussian process latent variable models for human pose estimation, pp. 132–143. (2007)

  14. Gordon, C.C., Churchill, T., Clauser, C.E., Bradtmiller, B., McConville, J.T., Tebberets, I., Walker, R.A.: Anthropometric survey of US army personnel: methods and summary statistics 1988. Technical report, US Army Natick Research, Development, and Engineering Center, (1989)

  15. Guan, P., Weiss, A., Balan, A.O., Black, M.J.: In International Conference on Computer Vision, Estimating human shape and pose from a single image. pp. 1381–1388 (2009)

  16. Hasler, N., Ackermann, H., Rosenhahn, B., Thormählen, T., Seidel, H.-P.: In Conference on Computer Vision and, Pattern Recognition. Multilinear pose and body shape estimation of dressed subjects from image sets, pp. 1823–1830. (2010)

  17. Hasler, N., Stoll, C., Sunkel, M., Rosenhahn, B., Seidel, H.-P.: A statistical model of human pose and body shape. In: Dutré P., Stamminger M. (eds.) Computer Graphics Forum 28(2), 337–346 (2009)

  18. Liu, D.C., Nocedal, J.: On the limited memory method for large scale optimization. Math. Program. 45(3), 503–528 (1989)

    Article  MathSciNet  MATH  Google Scholar 

  19. Robinette, K., Daanen, H., Paquet, E.: In 3-D Digital Imaging and Modeling, the CAESAR project: a 3-D surface anthropometry survey. pp. 180–186, (1999)

  20. Schmaltz, C., Rosenhahn, B., Brox, T., Weickert, J.: In machine vision and applications, Region-based pose tracking with occlusions using 3D models. 23(3), 557–577 (2012)

  21. Seo, H., Magnenat-Thalmann, N.: An automatic modeling of human bodies from sizing parameters. In Proceedings of the 2003 Symposium on interactive 3D graphics, pp. 19–26, (2003)

  22. Seo, H., Yeo, Y.I., Wohn, K.: 3D body reconstruction from photos based on range scan. Technologies for e-learning and digital entertainment, pp. 849–860, (2006)

  23. Shon, A.P., Grochow, K., Hertzmann, A., Rao, R.P.N.: Learning shared latent structure for image synthesis and robotic imitation. In neural information processing systems, pp. 1233–1240, (2005)

  24. van Kaick, O., Zhang, H., Hamarneh, G., Cohen-Or, D.: A survey on shape correspondence. Compt. Graphics Forum 30(6), 1681–1707 (2011)

    Article  Google Scholar 

  25. Wang, C.C.: Parameterization and parametric design of mannequins. Compt. Aided Des. 37(1), 83–98 (2005)

    Article  Google Scholar 

  26. Wei, W., Luo, X., Li, Z.: Layer-based mannequin reconstruction and parameterization from 3d range data. In advances in geometric modeling and processing, pp. 498–504, (2008)

  27. Weiss, A., Hirshberg, D., Black, M.: Home 3D body scans from noisy image and range data. In International Conference on Computer Vision, pp. 1951–1958, (2011)

  28. Wuhrer, S., Xi, P., Shu, C.: Human shape correspondence with automatically predicted landmarks. Mach. Vision Appl. 23(4), 821–830 (2012)

    Article  Google Scholar 

  29. Xi, P., Lee, W.-S., Shu, C.: In graphics, interface. Analysis of segmented human body scans, pp. 19–26. (2007)

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Acknowledgments

We thank the volunteers for participating in the experiment. Furthermore, we thank Pengcheng Xi for helpful discussions and for providing us with the training data, Neil Lawrence for providing us with the SGPLVM code, and the anonymous reviewers for helpful comments. This work has partially been funded by the Cluster of Excellence Multimodal Computing and Interaction within the Excellence Initiative of the German Federal Government.

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Authors and Affiliations

  1. Saarland University and Max-Planck Institut Informatik, Campus E 1.7, Saarbrücken, Germany

    Stefanie Wuhrer

  2. National Research Council of Canada, 1200 Montreal Road, Ottawa, Canada

    Chang Shu

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  1. Stefanie Wuhrer
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  2. Chang Shu
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Correspondence to Stefanie Wuhrer.

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Wuhrer, S., Shu, C. Estimating 3D human shapes from measurements. Machine Vision and Applications 24, 1133–1147 (2013). https://doi.org/10.1007/s00138-012-0472-y

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  • DOI: https://doi.org/10.1007/s00138-012-0472-y

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