Skip to main content

Shape from Specular Flow with Near-Field Environment Motion Field

  • Conference paper
Advances in Visual Computing (ISVC 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8887))

Included in the following conference series:

  • 3639 Accesses

Abstract

Reconstruction of curved, mirror-like surfaces in unknown lighting environments is a challenging problem. One well-known solution is the ‘shape from specular flow’ approach, which assumes far-field environment illumination. The assumption makes it impractical for the case of near-field environment. We show that with the presence of unknown nearby objects, the observed specular flow can be related to the surface shape and the environment motion through a group of nonlinear partial differential equations. This PDE system can be converted into a canonical form of hyperbolic equation. Stable, unique solution of such equation exists when the Cauchy boundary condition is given. Numerical methods are implemented to solve the PDE system for the case of translating near-field environment motions. Both the curved surface and the near-field environment are recovered. Experiments on both real and synthetic data support the proposed method.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Adato, Y., Vasilyev, Y., Ben-Shahar, O., et al.: Toward a theory of shape from specular flow. In: IEEE 11th International Conference on Computer Vision, ICCV 2007, pp. 1–8. IEEE (2007)

    Google Scholar 

  2. Adato, Y., Vasilyev, Y., Zickler, T., et al.: Shape from specular flow. IEEE Transactions on Pattern Analysis and Machine Intelligence 32(11), 2054–2070 (2010)

    Article  Google Scholar 

  3. Blake, A., Brelstaff, G.: Specular Stereo. IJCAI, 973-976 (1985)

    Google Scholar 

  4. Bonfort, T., Sturm, P.: Voxel carving for specular surfaces. In: Proceedings of the Ninth IEEE International Conference on Computer Vision, pp. 591–596. IEEE (2003)

    Google Scholar 

  5. Bonfort, T., Sturm, P., Gargallo, P.: General specular surface triangulation. In: Narayanan, P.J., Nayar, S.K., Shum, H.-Y. (eds.) ACCV 2006. LNCS, vol. 3852, pp. 872–881. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  6. Bruce, J.W., Giblin, P.J.: Curves and Singularities: a geometrical introduction to singularity theory. Cambridge University Press (1992)

    Google Scholar 

  7. Canas, G.D., Vasilyev, Y., Adato, Y., et al.: A linear formulation of shape from specular flow. In: 2009 IEEE 12th International Conference on Computer Vision, pp. 191–198. IEEE (2009)

    Google Scholar 

  8. Horn, B.K., Schunck, B.G.: Determining optical flow. In: 1981 Technical Symposium East. International Society for Optics and Photonics, pp. 319–331 (1981)

    Google Scholar 

  9. Ikeuchi, K.: Determining surface orientations of specular surfaces by using the photometric stereo method. IEEE Transactions on Pattern Analysis and Machine Intelligence (6), 661–669 (1981)

    Google Scholar 

  10. Liu, M., Wong, K.-Y.K., Dai, Z., Chen, Z.: Specular surface recovery from reflections of a planar pattern undergoing an unknown pure translation. In: Kimmel, R., Klette, R., Sugimoto, A. (eds.) ACCV 2010, Part II. LNCS, vol. 6493, pp. 137–147. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  11. Nayar, S.K., Sanderson, A.C., Weiss, L.E., et al.: Specular surface inspection using structured highlight and Gaussian images. IEEE Transactions on Robotics and Automation 6(2), 208–218 (1990)

    Article  Google Scholar 

  12. Oren, M., Nayar, S.K.: A theory of specular surface geometry. International Journal of Computer Vision 24(2), 105–124 (1997)

    Article  Google Scholar 

  13. Roth, S., Black, M.J.: Specular flow and the recovery of surface structure. In: 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 1869–1876. IEEE (1876)

    Google Scholar 

  14. Sanderson, A.C., Weiss, L.E., Nayar, S.K.: Structured highlight inspection of specular surfaces. IEEE Transactions on Pattern Analysis and Machine Intelligence 10(1), 44–55 (1988)

    Article  Google Scholar 

  15. Sankaranarayanan, A.C., Veeraraghavan, A., Tuzel, O., et al.: Specular surface reconstruction from sparse reflection correspondences. In: 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1245–1252. IEEE (2010)

    Google Scholar 

  16. Savarese, S., Chen, M., Perona, P.: Local shape from mirror reflections. International Journal of Computer Vision 64(1), 31–67 (2005)

    Article  Google Scholar 

  17. Solem, J.E., Aanæs, H., Heyden, A.: A variational analysis of shape from specularities using sparse data. In: Proceedings of the 2nd International Symposium on 3D Data Processing, Visualization and Transmission, 3DPVT 2004, pp. 26–33. IEEE (2004)

    Google Scholar 

  18. Vasilyev, Y., Adato, Y., Zickler, T., et al.: Dense specular shape from multiple specular flows. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008, pp. 1–8. IEEE (2008)

    Google Scholar 

  19. Vasilyev, Y., Zickler, T., Gortler, S., et al.: Shape from specular flow: Is one flow enough? In: 2011 IEEE Conference onComputer Vision and Pattern Recognition (CVPR), pp. 2561–2568. IEEE (2011)

    Google Scholar 

  20. Yamazaki, M., Iwata, S., Xu, G.: Dense 3D reconstruction of specular and transparent objects using stereo cameras and phase-shift method. In: Yagi, Y., Kang, S.B., Kweon, I.S., Zha, H. (eds.) ACCV 2007, Part II. LNCS, vol. 4844, pp. 570–579. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  21. Zisserman, A., Giblin, P., Blake, A.: The information available to a moving observer from specularities. Image and Vision Computing 7(1), 38–42 (1989)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Li, H., Song, T., Wu, Z., Ma, J., Ding, G. (2014). Shape from Specular Flow with Near-Field Environment Motion Field. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2014. Lecture Notes in Computer Science, vol 8887. Springer, Cham. https://doi.org/10.1007/978-3-319-14249-4_35

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-14249-4_35

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14248-7

  • Online ISBN: 978-3-319-14249-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics