Multiview Point Cloud Filtering for Spatiotemporal Consistency

Robert Skupin, Thilo Borgmann, Thomas Sikora

2014

Abstract

This work presents algorithms to resample and filter point cloud data reconstructed from multiple cameras and multiple time instants. In an initial resampling stage, a voxel or a surface mesh based approach resamples the point cloud data into a common sampling grid. Subsequently, the resampled data undergoes a filtering stage based on clustering to remove artifacts and achieve spatiotemporal consistency across cameras and time instants. The presented algorithms are evaluated in a view synthesis scenario. Results show that view synthesis with enhanced depth maps as produced by the algorithms leads to less artifacts than synthesis with the original source data.

References

  1. Belaifa, O., Skupin, R., Kurutepe, E., and Sikora, T. (2012). Resampling of Multiple Camera Point Cloud Data. In Consumer Communications and Networking Conference (CCNC), 2012 IEEE, pages 15-19. IEEE.
  2. Dodgson, N. A. (2005). Autostereoscopic 3D Displays. Computer, 38(8):31-36.
  3. Farnebäck, G. (2003). Two-Frame Motion Estimation Based On Polynomial Expansion. In Image Analysis, pages 363-370. Springer.
  4. Hastie, T., Tibshirani, R., and Friedman, J. J. H. (2001). The Elements of Statistical Learning, volume 1. Springer New York.
  5. Merkle, P., Morvan, Y., Smolic, A., et al. (2009). The Effects of Multiview Depth Video Compression On Multiview Rendering. Signal Processing: Image Communication, 24(1-2):73-88.
  6. Merrell, P., Akbarzadeh, A., Wang, L., Mordohai, P., Frahm, J.-M., Yang, R., Nister, D., and Pollefeys, M. (2007). Real-Time Visibility-Based Fusion of Depth Maps. Computer Vision, IEEE International Conference on, 0:1-8.
  7. Scharstein, D. and Szeliski, R. (2002). A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. International Journal of Computer Vision, 47(1):7-42.
  8. Seitz, S., Curless, B., Diebel, J., Scharstein, D., and Szeliski, R. (2006). A comparison and evaluation of multi-view stereo reconstruction algorithms.
  9. Smolic, A., Mueller, K., Merkle, P., Fehn, C., Kauff, P., Eisert, P., and Wiegand, T. (2006). 3d Video and Free Viewpoint Video-Technologies, Applications and Mpeg Standards. In Multimedia and Expo, 2006 IEEE International Conference on, pages 2161- 2164. IEEE.
  10. Starck, J. and Hilton, A. (2005). Virtual View Synthesis of People From Multiple View Video Sequences. Graphical Models, 67(6):600-620.
  11. Tao, H. and Sawhney, H. S. (2000). Global Matching Criterion and Color Segmentation Based Stereo. In Applications of Computer Vision, 2000, Fifth IEEE Workshop on., pages 246-253. IEEE.
  12. Vetro, A., Yea, S., and Smolic, A. (2008). Toward a 3D Video Format for Auto-Stereoscopic Displays. In Optical Engineering+ Applications, pages 70730F70730F. International Society for Optics and Photonics.
  13. Vogiatzis, G., Torr, P. H., and Cipolla, R. (2005). MultiView Stereo Via Volumetric Graph-Cuts. In Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, volume 2, pages 391-398. IEEE.
  14. Wang, Z., Bovik, A. C., Sheikh, H. R., and Simoncelli, E. P. (2004). Image Quality Assessment: From Error Visibility to Structural Similarity. Image Processing, IEEE Transactions on, 13(4):600-612.
  15. Zitnick, C., Kang, S., Uyttendaele, M., Winder, S., and Szeliski, R. (2004). High-Quality Video View Interpolation Using a Layered Representation. In ACM Transactions on Graphics (TOG), volume 23, pages 600-608. ACM.
Download


Paper Citation


in Harvard Style

Skupin R., Borgmann T. and Sikora T. (2014). Multiview Point Cloud Filtering for Spatiotemporal Consistency . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-009-3, pages 531-538. DOI: 10.5220/0004681805310538


in Bibtex Style

@conference{visapp14,
author={Robert Skupin and Thilo Borgmann and Thomas Sikora},
title={Multiview Point Cloud Filtering for Spatiotemporal Consistency},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={531-538},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004681805310538},
isbn={978-989-758-009-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014)
TI - Multiview Point Cloud Filtering for Spatiotemporal Consistency
SN - 978-989-758-009-3
AU - Skupin R.
AU - Borgmann T.
AU - Sikora T.
PY - 2014
SP - 531
EP - 538
DO - 10.5220/0004681805310538