Reconstruction of Relatively Straight Medium to Long Hair Models using Kinect Sensors

Chao Sun, Zhongrui Li, Won-Sook Lee

2015

Abstract

Most existing hair capturing methods reconstruct 3D hair models from multi-view stereo based on complex capturing systems composed of many digital cameras and light sources. In this paper, we introduce a novel hair capturing system using consumer RGB-D (Kinect sensors). Our capture system, consisting of three Kinect v2 sensors, is much simpler than previous hair capturing systems. We directly use the 3D point clouds captured by Kinect v2 sensors as the hair volume. Then we adopt a fast and robust image enhancement algorithm to adaptively improve the clarity of the hair strands geometry based on the estimated local strands orientation and frequency from the hair images captured by the Kinect colour sensors. In addition, we introduced a hair strand grow-and-connect algorithm to generate relatively complete hair strands. Furthermore, by projecting the 2D hair strands onto the 3D point clouds, we can obtain the corresponding 3D hair strands. The experimental results indicate that our method can generate plausible 3D models for long, relatively straight hair.

References

  1. AK., J. and F., F. (1990). Unsupervised texture segmentation using gabor filters. In Systems, Man and Cybernetics, 1990. Conference Proceedings., IEEE International Conference on, pages 14-19.
  2. Beeler, T., Bickel, B., Noris, G., Beardsley, P., Marschner, S., Sumner, R. W., and Gross, M. (2012). Coupled 3d reconstruction of sparse facial hair and skin. ACM Trans. Graph., 31(4):117:1-117:10.
  3. Besl, P. and McKay, N. D. (1992). A method for registration of 3-d shapes. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 14(2):239-256.
  4. Hong, L., Wan, Y., and Jain, A. (1998). Fingerprint image enhancement: Algorithm and performance evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20:777-789.
  5. Hu, L., Ma, C., Luo, L., and Li, H. (2014). Robust hair capture using simulated examples. ACM Transactions on Graphics (Proceedings SIGGRAPH 2014), 33(4).
  6. Jakob, W., Moon, J. T., and Marschner, S. (2009). Capturing hair assemblies fiber by fiber. In ACM SIGGRAPH Asia 2009 Papers, SIGGRAPH Asia 7809, pages 164:1-164:9, New York, NY, USA. ACM.
  7. Li, H., Vouga, E., Gudym, A., Luo, L., Barron, J. T., and Gusev, G. (2013). 3d self-portraits. ACM Transactions on Graphics (Proceedings SIGGRAPH Asia 2013), 32(6).
  8. Luo, L., Li, H., Paris, S., Weise, T., Pauly, M., and Rusinkiewicz, S. (2012). Multi-view hair capture using orientation fields. In Computer Vision and Pattern Recognition (CVPR).
  9. Luo, L., Li, H., and Rusinkiewicz, S. (2013a). Structureaware hair capture. ACM Transactions on Graphics (Proc. SIGGRAPH), 32(4).
  10. Luo, L., Zhang, C., Zhang, Z., and Rusinkiewicz, S. (2013b). Wide-baseline hair capture using strandbased refinement. In Computer Vision and Pattern Recognition (CVPR).
  11. Macknojia, R., Chavez-Aragon, A., Payeur, P., and Laganiere, R. (2013). Calibration of a network of kinect sensors for robotic inspection over a large workspace. In Robot Vision (WORV), 2013 IEEE Workshop on, pages 184-190.
  12. Paris, S., Bricen˜o, H., and Sillion, F. (2004). Capture of hair geometry from multiple images.
  13. Paris, S., Chang, W., Kozhushnyan, O. I., Jarosz, W., Matusik, W., Zwicker, M., and Durand, F. (2008). Hair photobooth: Geometric and photometric acquisition of real hairstyles. ACM Transactions on Graphics (Proceedings of SIGGRAPH), 27(3):30:1-30:9.
  14. Shapiro, A., Feng, A., Wang, R., Li, H., Bolas, M., Medioni, G., and Suma, E. (2014). Rapid avatar capture and simulation using commodity depth sensors. Computer Animation and Virtual Worlds.
  15. Tong, J., Zhou, J., Liu, L., Pan, Z., and Yan, H. (2012). Scanning 3d full human bodies using kinects. Visualization and Computer Graphics, IEEE Transactions on, 18(4):643-650.
  16. Wang, R., Choi, J., and Medioni, G. (2012). Accurate full body scanning from a single fixed 3d camera. In 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT), 2012 Second International Conference on, pages 432-439.
  17. Ward, K., Bertails, F., Kim, T.-Y., Marschner, S. R., Cani, M.-P., and Lin, M. C. (2007). A survey on hair modelling: styling, simulation, and rendering. IEEE Trans. on Visualization and Computer Graphics, 13(2):213-234.
  18. Wei, Y., Ofek, E., Quan, L., and Shum, H.-Y. (2005). Modeling hair from multiple views. ACM Trans. Graph., 24(3):816-820.
Download


Paper Citation


in Harvard Style

Sun C., Li Z. and Lee W. (2015). Reconstruction of Relatively Straight Medium to Long Hair Models using Kinect Sensors . In Proceedings of the 10th International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2015) ISBN 978-989-758-087-1, pages 158-164. DOI: 10.5220/0005312301580164


in Bibtex Style

@conference{grapp15,
author={Chao Sun and Zhongrui Li and Won-Sook Lee},
title={Reconstruction of Relatively Straight Medium to Long Hair Models using Kinect Sensors},
booktitle={Proceedings of the 10th International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2015)},
year={2015},
pages={158-164},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005312301580164},
isbn={978-989-758-087-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2015)
TI - Reconstruction of Relatively Straight Medium to Long Hair Models using Kinect Sensors
SN - 978-989-758-087-1
AU - Sun C.
AU - Li Z.
AU - Lee W.
PY - 2015
SP - 158
EP - 164
DO - 10.5220/0005312301580164