Non-negative lighting and specular object recognition
Shirdhonkar, S.
Jacobs, D.W.
Center for Autom. Res., Maryland Univ,, College Park, MD;
This paper appears in: Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on
Publication Date: 17-21 Oct. 2005
Volume: 2,
On page(s): 1323-1330 Vol. 2
Location: Beijing,
ISSN: 1550-5499
ISBN: 0-7695-2334-X
INSPEC Accession Number: 8824321
Digital Object Identifier: 10.1109/ICCV.2005.168
Current Version Published: 2005-12-05
Abstract
Recognition of specular objects is particularly difficult because their appearance is much more sensitive to lighting changes than that of Lambertian objects. We consider an approach in which we use a 3D model to deduce the lighting that best matches the model to the image. In this case, an important constraint is that incident lighting should be non-negative everywhere. In this paper, we propose a new method to enforce this constraint and explore its usefulness in specular object recognition, using the spherical harmonic representation of lighting. The method follows from a novel extension of Szego's eigenvalue distribution theorem to spherical harmonics, and uses semidefinite programming to perform a constrained optimization. The new method is faster as well as more accurate than previous methods. Experiments on both synthetic and real data indicate that the constraint can improve recognition of specular objects by better separating the correct and incorrect models
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