Cast shadows and linear subspaces for object recognition

Image analysis – Applications – 3-d or stereo imaging analysis

Reexamination Certificate

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Details

C382S118000, C382S190000, C345S426000

Reexamination Certificate

active

07006684

ABSTRACT:
The present invention is a method of deriving a reflectance function that analytically approximates the light reflected from an object model in terms of the spherical harmonic components of light. The reflectance function depends upon the intensity of light incident at each point on the model, but excludes light originating from below a local horizon, therefore not contributing to the reflectance because of the cast shadows. This reflectance function is used in the process of machine vision, by allowing a machine to optimize the reflectance function and arrive at an optimal rendered image of the object model, relative to an input image. Therefore, the recognition of an image produced under variable lighting conditions is more robust. The reflectance function of the present invention also has applicability in other fields, such as computer graphics.

REFERENCES:
patent: 6137896 (2000-10-01), Chang et al.
patent: 6639594 (2003-10-01), Zhang et al.
Georghiades et al., Illumination Cones for Recognition Under Variable Lighting: Faces, 1998, Computer Vision and Pattern Recognition, pp. 52-58.
Mukaigawa et al., Photometric image-based rendering for image generation in arbitrary illumination, Computer Vision, 2001 ICCV 2001. Proceedings. Eighth IEEE International Conference on, vol. 2, Jul. 7-14, 2001 pp. 652-659.
Bolvin et al., Image-Based Rendering of Diffuse, Specular and Glossy Surfaces from a Single Image, ACM SIGGRAPH, Aug. 2001, pp. 107-116.
1. M.E. Rose, “Elementary Theory of Angular Momentum”, ISBN 0471 73524 8 pp. 228-235, 1957.
2. Hideki Hayakawa, Photometric Stereo Under a Light Source With Arbitrary Motion,Journal of Optical Society of America, vol. 11, No. 11, pp. 3079-3089, Nov. 1994.
3. Peter W. Hallinan, “A Low-Dimensional Representation of Human Faces For Arbitrary Lighting Conditions”,IEEE Conference on Computer Vision and Pattern Recognition, pp. 995-998, (1994).
4. Jan J. Koenderink and Andrea J. Van Doorn, “The Generic Bilinear Calibration-Estimation Problem”,International Journal of Computer Visionvol. 23, No. 3,pp. 217-234, (1997).
5. Amnon Shashua, “On Photometric Issues in 3D Visual Recognition from a Single 2D Image”,International Journal of Computer Vision, vol. 21, No. 1-2, pp. 99-122, (1997).
6. Peter N. Belhumeur and David J. Kriegman, “What is the set of Images of an Object Under All Possible Illumination Conditions”,International Journal of Computer Vision, vol. No. 28, No. 3, pp 245-260, (1998).
7. M.S. Langer, “When Shadows Become Interreflections”,International Journal of Computer Vision, vol. 34, No. 2-3, pp. 193-204 (1999).
8. Ronen Basri and David Jacobs, “Lambertian Reflectance and Linear Subspaces”,IEEE Conference on Computer Vision,II, pp. 383-390, 2001.
9. R. Ramamoorthi and P. Hanrahan, “On The Relationship Between Radiance and Irradiance: Determining The Illumination from Images of a Convex Lambertian Object”,Journal of Optical Society of America, vol. 18, No. 10, pp. 2448-2458, 2001.
10. K.K. Thornber and D.W. Jacobs, “Broadened, Specular Reflection and Linear Subspaces”, NEC Research Institute, Inc., Technical Report #2001-033.

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