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Helmholtz stereopsis: Exploiting reciprocity for surface reconstruction 7th

7th European Conference on comp.ter vision, ECCV 2002

作者： Zickler, Todd Belhumeur, Peter N. Kriegman, David J. Center for Comp. Vision and Control Yale University New HavenCT06520-8285 United States Department of Computer Science Columbia University New YorkNY10027 United States Beckman Institute University of Illinois Urbana-Champaign UrbanaIL61801 United States

ISBN: (纸本)3540437460

We present a method – termed Helmholtz stereopsis – for reconstructing the geometry of objects from a collection of images. Unlike most existing methods for surface reconstruction (e.g., stereo vision, structure from motion, photometric stereo), Helmholtz stereopsis makes no assumptions about the nature of the bidirectional reflectance distribution functions (BRDFs) of objects. This new method of multinocular stereopsis exploits Helmholtz reciprocity by choosing pairs of light source and camera positions that guarantee that the ratio of the emitted radiance to the incident irradiance is the same for corresponding points in the two images. The method provides direct estimates of both depth and field of surface normals, and consequently weds the advantages of both conventional and photometric stereopsis. Results from our implementations lend empirical support to our technique. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Light sources

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Image-based modeling and rendering of surfaces with arbitrary BRDFs

Image-based modeling and rendering of surfaces with arbitrar...

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2001 IEEE comp.ter Society Conference on comp.ter vision and Pattern Recognition

作者： Koudelka, Melissa L. Belhumeur, Peter N. Magda, Sebastian Kriegman, David J. Center for Comp. Vision and Control EE and CS Yale University New Haven CT 06520-8267 United States

A goal of image-based rendering is to synthesize as realistically as possible man made and natural objects. This paper presents a method for image-based modeling and rendering of objects with arbitrary (possibly anisotropic and spatially varying) BRDFs. An object is modeled by sampling the surface's incident light field to reconstruct a non-parametric apparent BRDF at each visible point on the surface. This can be used to render the object from the same viewpoint but under arbitrarily specified illumination. We demonstrate how these object models can be embedded in synthetic scenes and rendered under global illumination which captures the interreflections between real and synthetic objects. We also show how these image-based models can be automatically comp.sited onto video footage with dynamic illumination so that the effects (shadows and shading) of the lighting on the comp.sited object match those of the scene.

关键词： Image reconstruction

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Bas-relief ambiguity

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International Journal of comp.ter vision 1999年第1期35卷 33-44页

作者： Belhumeur, Peter N. Kriegman, David J. Yuille, Alan L. Center for Comp. Vision and Control Dept. of Electrical Engineering Yale University New Haven CT 06520 United States Beckman Institute Department of Computer Science Univ. of Illinois Urbana-Champaign Urbana IL 61801 United States Smith-Kettlewell Eye Res. Institute San Francisco CA 94115 United States

When an unknown object with Lambertian reflectance is viewed orthographically, there is an implicit ambiguity in determining its 3-d structure: we show that the object's visible surface f(x, y) is indistinguishable from a `generalized bas-relief' transformation of the object's geometry, f¯(x, y) = λf(x, y)+μx+vy, and a corresponding transformation on the object's albedo. For each image of the object illuminated by an arbitrary number of distant light sources, there exists an identical image of the transformed object illuminated by similarly transformed light sources. This result holds both for the illuminated regions of the object as well as those in cast and attached shadows. Furthermore, neither small motion of the object, nor of the viewer will resolve the ambiguity in determining the flattening (or scaling) λ of the object's surface. Implications of this ambiguity on structure recovery and shape representation are discussed.

关键词： Object recognition

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