Performance Analysis of Virtual Human Bodies with Clothing and Hair from Images to Animation

Kulalvaimozhi. V. P., Germanus Alex. M, John Peter. S

Abstract


Virtual human bodies, clothing, and hair are widely used in a number of scenarios such as 3D animated movies, gaming, and online fashion. Machine learning can be used to construct data-driven 3D human bodies, clothing, and hair. In this thesis, we provide a solution to 3D shape and pose estimation under the most challenging situation where only a single image is available and the image is captured in a natural environment with unknown camera calibration. We also demonstrate that a simplified 2D clothing model helps to increase the accuracy of 2D body shape estimation significantly.

Full Text:

PDF

References


Y. Chen and R. Cipolla. Single and sparse view 3d reconstruction by learning shape priors. Computer Vision and Image Understanding, 115(5):586–602, May 2011.

Y. Chen, T.-K. Kim, and R. Cipolla. Inferring 3d shapes and deformations from single views. In EuropeanConference on Computer Vision, ECCV, pages 300–313, 2010

G. Daviet, F. Bertails-Descoubes, and L. Boissieux. A hybrid iterative solver for robustly capturing coulomb friction in hair dynamics. ACM Trans. Graph., 30(6):139:1–139:12, Dec. 2011.

P. Guan, L. Reiss, D. A. Hirshberg, A. Weiss, and M. J. Black. Drape: Dressing any person. ACM Trans. Graph.(Proc. SIGGRAPH), 31(4):35:1–35:10, July 2012.

P. Guan, L. Sigal, V. Reznitskaya, and J. K. Hodgins. Multi-linear data-driven dynamic hair model with efficient hair-body collision handling. In Proceedings of the 2005 ACM SIGGRAPH/Eurographics symposium on Computer animation, SCA ’12, pages 295–304. ACM, 2012.

M. Hofmanna and D. M. Gavrila. 3d human model adaptation by frame selection and shape-texture optimization. Computer Vision and Image Understanding, 115(11):1559–1570, Nov 2011

X. Huang, I. D. Walker, and S. Birchfield. Occlusion-aware reconstruction and manipulation of 3d articulated objects. In IEEE International Conference on Robotics and Automation, pages 1365–1371. IEEE, 2012.

S. Izadi, D. Kim, O. Hilliges, D. Molyneaux, R. Newcombe, P. Kohli, J. Shotton, S. Hodges, D. Freeman, A. Davison, and A. Fitzgibbon. Kinectfusion: real-time 3d reconstruction and interaction using a moving depth camera. In Proceedings of the 24th annual ACM symposium on User interface software and technology, UIST ’ 11, pages 559–568, New York, NY, USA, 2011. ACM.

L. Kavan, D. Gerszewski, A. W. Bargteil, and P.-P. Sloan. Physics-inspired upsampling for cloth simulation in games. ACM Trans. Graph., 30(4):93:1–93:10, July 2011.

S. Miller, M. Fritz, T. Darrell, and P. Abbeel. Parametrized shape models for clothing. In IEEE International Conference on Robotics and Automation, pages 4861–4868, Shanghai, China, 2011. IEEE.

F. Moreno-Nogueer and J. Porta. Probabilistic simultaneous pose and non-rigid shape recovery. In IEEE Conference on Computer Vision and Pattern Recognition, CVPR, pages 1289–1296, Jun 2011.




DOI: https://doi.org/10.23956/ijarcsse.v8i6.723

Refbacks

  • There are currently no refbacks.




© International Journals of Advanced Research in Computer Science and Software Engineering (IJARCSSE)| All Rights Reserved | Powered by Advance Academic Publisher.