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Mathematical Problems in Engineering
Volume 2013, Article ID 715808, 8 pages
http://dx.doi.org/10.1155/2013/715808
Research Article

Optimization and Soft Constraints for Human Shape and Pose Estimation Based on a 3D Morphable Model

1Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China
2Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing 100044, China
3College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China

Received 10 April 2013; Revised 9 August 2013; Accepted 9 August 2013

Academic Editor: Yang Xu

Copyright © 2013 Dianyong Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. J. Gall, C. Stoll, E. De Aguiar, C. Theobalt, B. Rosenhahn, and H.-P. Seidel, “Motion capture using joint skeleton tracking and surface estimation,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR '09), pp. 1746–1753, Miami, Fla, USA, June 2009. View at Publisher · View at Google Scholar · View at Scopus
  2. A. Jain, T. Thormählen, H.-P. Seidel, and C. Theobalt, “MovieReshape: tracking and reshaping of humans in videos,” ACM Transactions on Graphics, vol. 29, no. 6, Article ID 1866174, 2010. View at Publisher · View at Google Scholar · View at Scopus
  3. N. Hasler, C. Stoll, M. Sunkel, B. Rosenhahn, and H.-P. Seidel, “A statistical model of human pose and body shape,” Computer Graphics Forum, vol. 28, no. 2, pp. 337–346, 2009. View at Publisher · View at Google Scholar · View at Scopus
  4. T. B. Moeslund and E. Granum, “A survey of computer vision-based human motion capture,” Computer Vision and Image Understanding, vol. 81, no. 3, pp. 231–268, 2001. View at Publisher · View at Google Scholar · View at Scopus
  5. T. B. Moeslund, A. Hilton, and V. Krüger, “A survey of advances in vision-based human motion capture and analysis,” Computer Vision and Image Understanding, vol. 104, no. 2-3, pp. 90–126, 2006. View at Publisher · View at Google Scholar · View at Scopus
  6. G. Pons-Moll and B. Rosenhahn, Book Chapter on Model Based Pose Estimation to Appear in Guide to Visual Analysis of Humans: Looking at People, Springer, New York, NY, USA, 2011.
  7. D. Anguelov, P. Srinivasan, D. Koller, S. Thrun, J. Rodgers, and J. Davis, “SCAPE: shape completion and animation of people,” ACM Transactions on Graphics, vol. 24, no. 3, pp. 241–253, 2005. View at Google Scholar
  8. A. O. Bǎlan, L. Sigal, M. J. Black, J. E. Davis, and H. W. Haussecker, “Detailed human shape and pose from images,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '07), pp. 1–8, Minneapolis, Minn, USA, June 2007. View at Publisher · View at Google Scholar · View at Scopus
  9. P. Guan, A. Weiss, A. O. Balan, and M. J. Black, “Estimating human shape and pose from a single image,” in Proceedings of the IEEE 12th International Conference on Computer Vision (ICCV '09), 2009.
  10. L. Sigal, A. Balan, and M. J. Black, “Combined discriminative and generative articulated pose and non-rigid shape estimation,” in Proceedings of the 21st Annual Conference on Neural Information Processing Systems (NIPS '07), December 2007. View at Scopus
  11. Y. Chen, T.-K. Kim, and R. Cipolla, “Inferring 3D shapes and deformations from single views,” in Proceedings of the 11th European Conference on Computer Vision, pp. 300–313, 2010.
  12. S. Zhou, H. Fu, L. Liu, D. Cohen-Or, and X. Han, “Parameter reshaping of human bodies in images,” ACM Transactions on Graphics (TOG), vol. 29, no. 4, 2010. View at Google Scholar
  13. G. Pons-Moll, A. Baak, T. Helten, M. Müller, H.-P. Seidel, and B. Rosenhahn, “Multisensor-fusion for 3D full-body human motion capture,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '10), pp. 663–670, San Francisco, Calif, USA, June 2010. View at Publisher · View at Google Scholar · View at Scopus
  14. J. Gall, B. Rosenhahn, and H. P. Seidel, “An introduction to interacting simulated annealing,” in Human Motion, vol. 36 of Understanding, Modeling, Capture and Animation, Computational Imaging and Vision, pp. 319–345, Springer, 2008. View at Google Scholar
  15. J. Gall, B. Rosenhahn, T. Brox, and H.-P. Seidel, “Optimization and filtering for human motion capture: AAA multi-layer framework,” International Journal of Computer Vision, vol. 87, no. 1-2, pp. 75–92, 2010. View at Publisher · View at Google Scholar · View at Scopus
  16. D. Olga, Motion capture in uncontrolled environments [M.S. thesis], Eidgenossische Technische Hochschule Zurich; INFK; Computer Vision and Geometry Group, 2010.
  17. Y. Liu, C. Stoll, J. Gall, H.-P. Seidel, and C. Theobalt, “Markerless motion capture of interacting characters using multi-view image segmentation,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR '11), pp. 1249–1256, Providence, RI, USA, June 2011. View at Publisher · View at Google Scholar · View at Scopus
  18. I. Baran and J. Popović, “Automatic rigging and animation of 3D characters,” ACM Transactions on Graphics, vol. 26, no. 3, 2007. View at Google Scholar
  19. D. Y. Zhang, Z. J. Miao, and S. Y. Chen, “Human model adaptation for multi-view markerless motion capture,” Mathematical Problems in Engineering, vol. 2013, Article ID 564214, 7 pages, 2013. View at Publisher · View at Google Scholar
  20. T. Brox, B. Rosenhahn, and D. Cremers, “Contours, optic flow, and prior knowledge:cues for capturing 3D human motion in videos,” in Human Motion, vol. 36 of Understanding, Modeling, Capture and Animation, pp. 265–293, Spring, Computational Imaging and Vision, 2007. View at Google Scholar
  21. L. Sigal, A. O. Balan, and M. J. Black, “HumanEva: synchronized video and motion capture dataset and baseline algorithm for evaluation of articulated human motion,” International Journal of Computer Vision, vol. 87, no. 1-2, pp. 4–27, 2010. View at Publisher · View at Google Scholar · View at Scopus
  22. E. Parzen, “On estimation of a probability density function and mode,” Annals of Mathematical Statistics, vol. 33, pp. 1065–1076, 1962. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  23. M. Rosenblatt, “Remarks on some nonparametric estimates of a density function,” Annals of Mathematical Statistics, vol. 27, pp. 832–837, 1956. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  24. A. Baak, T. Helten, M. Mueller, G. Pons-Moll, H. P. Seidel, and B. Rosenhahn, “Analyzing and evaluating markerless motion tracking using inertial sensors,” in Proceedings of the 11th European conference on Trends and Topics in Computer Vision (ECCV '10), pp. 139–152, 2010. View at Google Scholar