Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

Statistical multiple light source detection

Statistical multiple light source detection

For access to this article, please select a purchase option:

Buy article PDF
$19.95
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Computer Vision — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Multiple light source detection has many applications in image synthesis and augmented reality. Current techniques can provide accurate results but have limited applicability in real-life scenarios where interaction with the scene is not possible. The authors provide a statistical framework for multiple light source detection that relies on the common features of objects belonging to a particular class and illustrate it using the class of human faces. Experiments with real data demonstrate that a light distribution with up to three light sources can be detected within 13° mean error. Application of the proposed framework to the problem of 3D reconstruction from multiple images under arbitrary lighting demonstrates the effectiveness of the framework compared with current techniques.

References

    1. 1)
      • Liu, C., Wechsler, H.: `Enhanced Fisher linear discriminant models for face recongnition', Int. Conf. on Pattern Recognition, August 1998.
    2. 2)
      • Zhang, L., Samaras, D.: `Face recognition under variable lighting using harmonic image exemplars', CVPR, 2003, I, p. 19–25.
    3. 3)
      • Sato, I., Sato, Y., Ikeuchi, K.: `Illumination distribution from brightness in shadows: adaptive estimation of illumination distribution with unknown reflectance properties in shadow regions', Int. Conf. Computer Vision, 1995, 2, p. 875–882.
    4. 4)
      • Kemelmacher, I., Basri, R.: `Molding face shapes by example', ECCV'06, May 2006, 1, p. 277–288.
    5. 5)
      • Debevec, P.E.: `Rendering synthetic objects into real scenes: Bridge traditional and image-based graphics with global illumination and high dynamic range photography', SIGGRAPH 98, July 998, p. 189–198.
    6. 6)
      • A.P. Pentland . Finding the illuminant direction. J. Opt. Soc. Am. , 448 - 455
    7. 7)
      • Schemer, Y.Y., Nayar, S.K., Belhemeur, P.N.: `A theory of multiplexed illumination', 9thIEEE Inter. Conf. on Computer Vision (ICCV'03), 2003, 2, p. 808–815.
    8. 8)
      • Nishino, K., Nayar, S.K.: `Eyes for relighting', SIGGRAPH, 2004, 23, p. 704–711.
    9. 9)
      • Marchener, S.R., Greenberg, D.P.: `Inverse lighting for photography', 5thColor Imaging Conf., Society for Imaging Science and Technology, 1997.
    10. 10)
    11. 11)
      • Sim, T., Basker, S., Bast, M.: `The CMU pose, illumination, and expression (PIE) database', Proc. 5th Int. Conf. on Automatic Face Gesture Recognition, 2002.
    12. 12)
      • T. Sim , T. Kanade . (2001) Illuminating the face, Tech. Rep. CMU-RI-TR-01-31..
    13. 13)
      • Lee, K.C., Ho, J., Kriegman, D.: `Nine points of light: acquiring subspaces for faces recognition under variable lighting', Proc IEEE Conf. Computer Vision and Pattern Recognition, 2001.
    14. 14)
    15. 15)
    16. 16)
      • Georghiades, A.S., Kriegman, D.J., Belhumeur, P.N.: `Illumination cones for recognition under variable lighting: faces', Proc. IEEE Conf. on Computer Vision and Pattern Recognition, 1998, p. 52–58.
    17. 17)
      • R.O. Duda , P.E. Hart . (1973) Pattern classification and scene analysis.
    18. 18)
      • S.C. Kee , K.M. Lee , S.U. Lee . Illumination invariant face recognition using photometric stereo. IEICE Trans. Inf. Syst. , 7 , 1466 - 1474
    19. 19)
      • K.E. Torrance , E.M. Sparrow . Theory for off-specular reflection from roughened surface. J. Opt. Soc. Am. , 1105 - 1114
    20. 20)
      • Cootes, T., Walker, K., Taylor, C.: `View-based active appearance models', 4thInt. Conf. on Automatic Face and Gesture Recognition, 2000, p. 227–232.
    21. 21)
      • B.T. Phong . Illumination for computer generated images. Commun. ACM , 311 - 317
    22. 22)
      • Bouganis, C.-S., Brookes, M.: `Class-based multiple light detection: an application to faces', British Machine Vision Conf., 2003, 1, p. 113–122.
    23. 23)
    24. 24)
      • Cyberwarehttp://www.cyberware.com/(1999).
    25. 25)
      • C.-S. Bouganis , M. Brookes . Mulitple light source detection. IEEE Trans. Pattern Anal. Mach. Intell. , 4 , 509 - 514
    26. 26)
      • R. Basri , D. Jacobs , I. Kemelmacher . Photometric stereo with general, unknown lighting. Int. J. Comput. Vis. , 3 , 239 - 257
    27. 27)
      • Yang, J., Yu, H., Kunz, W.: `An Effcient LDA algorithm for face recognition', 6thInt. Conf. on Control, Automation, Robotics and Vision (ICARCV 2000), 2000.
    28. 28)
      • Debevec, P., Hawkins, T., Tchou, C., Duiker, H.P., Sarokin, W., Sagar, M.: `Acquiring the reflectance field of a human face', SIGGRAPH 00, 2000, p. 145–156.
    29. 29)
      • I.T. Jolliffe . (1986) Principle component analysis.
    30. 30)
      • K. Fukunaga . (1991) Introduction to statistical pattern recognition.
    31. 31)
      • T. Riklin-Raviv , A. Shashua . The quotient image: class-based re-rendering and recognition with varying illuminations. IEEE Trans. Pattern Anal. Mach. Intell. , 2 , 129 - 131
    32. 32)
    33. 33)
      • J.-H. Jiang , R. Tsenkova , Y. Ozaki . Principal discriminant variate method for classification of multicollinear data: principle and applications. Anal. Sci. , i471 - i474
    34. 34)
      • W.Y. Zhao , R. Chellappa . Symmetric shape-from-shading using self-ratio image. Int. J. Comput. Vis. , 1 , 55 - 75
    35. 35)
      • P.N. Belhumeur , D.J. Kriegman . What is the set of images of an object under all possible lighting conditions?. Proc. IEEE Conf. on Computer Vision and Pattern Recognition , 270 - 277
    36. 36)
      • Tsumura, N., Dang, M.N., Makino, T., Miyake, Y.: `Estimating the directions to light sources using images of eye for reconstructing 3D human face', IS&T/SIDs 11 Color Imaging Conf., 2003, p. 77–81.
    37. 37)
      • Kovesi, P.: `Shapelets correlated with surface normals produce surfaces', IEEE Int. Conf. on Computer Vision, 2005, 2, p. 994–1001.
    38. 38)
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cvi_20065001
Loading

Related content

content/journals/10.1049/iet-cvi_20065001
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address