Name
Abstract | ||
|---|---|---|
Complex reflectance phenomena such as specular reflections confound many vision problems since they produce image 'features' that do not correspond directly to intrinsic surface properties such as shape and spectral reflectance. A common approach to mitigate these effects is to explore functions of an image that are invariant to these photometric events. In this paper we describe two such invariants" one invariant to specular reflections, and the other invariant to both specular reflections and diffuse shading" that result from exploiting color information in images of dichromatic surfaces. These invariants are derived from subspaces of RGB color space, and they enable the application of Lambertian-based vision techniques to a broad class of specular, non-Lambertian scenes. Using implementations of recent algorithms taken from the literature, we demonstrate the practical utility of these invariants for a wide variety of applications, including stereo, shape from shading, material-based segmentation, and motion estimation. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/s11263-007-0087-3 | International Journal of Computer Vision |
Keywords | Field | DocType |
specular reflection,photometric stereo,photometric invariants · shape invariants · color spaces · dichromatic reflection · multispectral imaging · surface reconstruction · photometric stereo · shape from shading · stereo · color-based segmentation · color-based optical flow,color information,spectral reflectance,photometric event,rgb color space,lambertian-based vision technique,complex reflectance phenomenon,photometric invariants,vision problem,broad class,color subspaces,information geometry,image segmentation,photometry,shape from shading,surface reconstruction,shape,reflectivity,layout,lighting,motion estimation,reflection,image reconstruction,optical flow,color space,multispectral images | Iterative reconstruction,Computer vision,Color space,Pattern recognition,Computer science,RGB color space,Specular reflection,Image segmentation,Artificial intelligence,Invariant (mathematics),Motion estimation,Photometric stereo | Journal |
Volume | Issue | ISSN |
79 | 1 | 0920-5691 |
Citations | PageRank | References |
28 | 1.09 | 54 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Todd Zickler | 1 | 1555 | 71.72 |
| Satya P. Mallick | 2 | 228 | 10.70 |
| David Kriegman | 3 | 7693 | 451.96 |
| Peter N. Belhumeur | 4 | 12242 | 1001.27 |