Color Subspaces as Photometric Invariants

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• 作者：Todd Zickler ; Satya P. Mallick ; David J. Kriegman and Peter N. Belhumeur
• 关键词：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
• 刊名：International Journal of Computer Vision
• 出版年：2008
• 出版时间：August, 2008
• 年：2008
• 卷：79
• 期：1
• 页码：13-30
• 全文大小：874.2 KB

文摘

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 a class of such invariants that result from exploiting color information in images of dichromatic surfaces. These invariants are derived from illuminant-dependent ‘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, photometric stereo, material-based segmentation, and motion estimation.