NON-PARAMETRIC ACQUISITION OF NEAR-DIRAC PIXEL CORRESPONDENCES

Bradley Atcheson, Wolfgang Heidrich

2012

Abstract

Many computer vision and graphics applications require the acquisition of correspondences between the pixels of a 2D illumination pattern and those of captured 2D photographs. Trivial cases with only one-to-one correspondences require only a few measurements. In more general scenes containing complex inter-reflections, capturing the full reflectance field requires more extensive sampling and complex processing schemes. We present a method that addresses the middle-ground: scenes where each pixel maps to a small, compact set of pixels that cannot easily be modeled parametrically. The coding method is based on optically-constructed Bloom filters and frequency coding. It is non-adaptive, allowing fast acquisition, robust to measurement noise, and can be decoded with only moderate computational power. It requires fewer measurements and scales up to higher resolutions more efficiently than previous methods.

References

  1. Atcheson, B., Ihrke, I., Heidrich, W., Tevs, A., Bradley, D., Magnor, M., and Seidel, H.-P. (2008). Time-resolved 3D capture of non-stationary gas flows. ACM Trans. Graphics, 27:132.
  2. Bitner, J., Ehrlich, G., Reingold, E., and 1976 (1976). Efficient generation of the binary reflected Gray code and its applications. Communications of the ACM, 19:517-521.
  3. Bloom, B. H. (1970). Space/time trade-offs in hash coding with allowable errors. Communications of the ACM, 13:422-426.
  4. Candes, E. J. and Tao, T. (2005). Decoding by linear programming. IEEE Transactions on Information Theory, 51:4203-4215.
  5. Chuang, Y.-Y., Zongker, D. E., Hindorff, J., Curless, B., Salesin, D. H., and Szeliski, R. (2000). Environment matting extensions: Towards higher accuracy and real-time capture. In Intl Conf. on Computer Graphics and Interactive Techniques, pages 121-130.
  6. Debevec, P., Hawkins, T., Tchou, C., Duiker, H.-P., Sarokin, W., and Sagar, M. (2000). Acquiring the reflectance field of a human face. In SIGGRAPH 7800, pages 145- 156.
  7. Hall-Holt, O. and Rusinkiewicz, S. (2001). Stripe boundary codes for real-time structured-light range scanning of moving objects. In Proc. ICCV, volume 2, pages 359- 366.
  8. Kay, S. M. (1993). Fundamentals of statistical signal processing, Volume I: Estimation theory. Prentice Hall PTR.
  9. Kirsch, A. and Mitzenmacher, M. (2006). Less hashing, same performance: Building a better bloom filter. In Algorithms - ESA 2006, volume 4168, pages 456-467. Springer.
  10. Peers, P. and Dutré, P. (2005). Inferring reflectance functions from wavelet noise. In Bala, K. and Dutré, P., editors, Proc. EGSR, page 173182.
  11. Roy, R. and Kailath, T. (1989). ESPRIT-estimation of signal parameters via rotational invariance techniques. IEEE Trans. Acoustics, Speech, and Signal Processing, 37:984-995.
  12. Rusinkiewicz, S., Hall-Holt, O., and Levoy, M. (2002). Real-time 3D model acquisition. ACM Trans. Graphics, 21:438-446.
  13. Scharstein, D. and Szeliski, R. (2003). High-accuracy stereo depth maps using structured light. In Proc. CVPR, volume 1, pages I-195--I-202.
  14. Sen, P., Chen, B., Garg, G., Marschner, S. R., Horowitz, M., Levoy, M., and Lensch, H. P. A. (2005). Dual photography. ACM Trans. Graphics, 24:745-755.
  15. Thomas, M., Misra, S., Kambhamettu, C., and Kirby, J. (2005). A robust motion estimation algorithm for piv. Measurement Science and Technology, 16:865-877.
  16. Wexler, Y., Fitzgibbon, A., and Zisserman, A. (2002). Image-based environment matting. In Proc. 13th Eurographics Workshop on Rendering, pages 279-290.
  17. Zhu, J. and Yang, Y.-H. (2004). Frequency-based environment matting. In Proc. Pacific Graphics, pages 402- 410.
  18. Zongker, D. E., Werner, D. M., Curless, B., and Salesin, D. H. (1999). Environment matting and compositing. In Intl Conf. Computer Graphics and Interactive Techniques, pages 205-214.
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Paper Citation


in Harvard Style

Atcheson B. and Heidrich W. (2012). NON-PARAMETRIC ACQUISITION OF NEAR-DIRAC PIXEL CORRESPONDENCES . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012) ISBN 978-989-8565-04-4, pages 247-254. DOI: 10.5220/0003825002470254


in Bibtex Style

@conference{visapp12,
author={Bradley Atcheson and Wolfgang Heidrich},
title={NON-PARAMETRIC ACQUISITION OF NEAR-DIRAC PIXEL CORRESPONDENCES},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)},
year={2012},
pages={247-254},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003825002470254},
isbn={978-989-8565-04-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)
TI - NON-PARAMETRIC ACQUISITION OF NEAR-DIRAC PIXEL CORRESPONDENCES
SN - 978-989-8565-04-4
AU - Atcheson B.
AU - Heidrich W.
PY - 2012
SP - 247
EP - 254
DO - 10.5220/0003825002470254