Beyond Lambert: Reconstructing Specular Surfaces Using Color

Authors:
Satya P. Mallick;Todd E. Zickler;David J. Kriegman;Peter N. Belhumeur
Affiliations:
University of California at San Diego;Harvard University;University of California at San Diego;Columbia University
Venue:
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Year:
2005

Citing 0
Cited 20

Object surface recovery using a multi-light photometric stereo technique for non-Lambertian surfaces subject to shadows and specularities

Image and Vision Computing
Mesostructure from specularity using gradient illumination

PROCAMS '08 Proceedings of the 5th ACM/IEEE International Workshop on Projector camera systems
Principles of appearance acquisition and representation

ACM SIGGRAPH 2008 classes
A photometric approach for estimating normals and tangents

ACM SIGGRAPH Asia 2008 papers
Data-driven diffuse-specular separation of spherical gradient illumination

SIGGRAPH '09: Posters
Principles of Appearance Acquisition and Representation

Foundations and Trends® in Computer Graphics and Vision
Joint Estimation of Shape and Reflectance using Multiple Images with Known Illumination Conditions

International Journal of Computer Vision
Wavelet-Texture Method: Appearance Compression by Polarization, Parametric Reflection Model, and Daubechies Wavelet

International Journal of Computer Vision
Real-time specular highlight removal using bilateral filtering

ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Photometric stereo from maximum feasible Lambertian reflections

ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Towards full 3D Helmholtz stereovision algorithms

ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
An introduction to image-based 3D surface reconstruction and a survey of photometric stereo methods

3D Research
Specularity removal in images and videos: a PDE approach

ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Correspondence search in the presence of specular highlights using specular-free two-band images

ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
Fast high-resolution appearance editing using superimposed projections

ACM Transactions on Graphics (TOG)
Surface reflectance and normal estimation from photometric stereo

Computer Vision and Image Understanding
Estimating specular roughness and anisotropy from second order spherical gradient illumination

EGSR'09 Proceedings of the Twentieth Eurographics conference on Rendering
Rapid acquisition of specular and diffuse normal maps from polarized spherical gradient illumination

EGSR'07 Proceedings of the 18th Eurographics conference on Rendering Techniques
Surface enhancement using real-time photometric stereo and reflectance transformation

EGSR'06 Proceedings of the 17th Eurographics conference on Rendering Techniques
A new projection space for separation of specular-diffuse reflection components in color images

ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part IV

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present a photometric stereo method for non-diffuse materials that does not require an explicit reflectance model or reference object. By computing a data-dependent rotation of RGB color space, we show that the specular reflection effects can be separated from the much simpler, diffuse (approximately Lambertian) reflection effects for surfaces that can be modeled with dichromatic reflectance. Images in this transformed color space are used to obtain photometric reconstructions that are independent of the specular reflectance. In contrast to other methods for highlight removal based on dichromatic color separation (e.g., color histogram analysis and/or polarization), we do not explicitly recover the specular and diffuse components of an image. Instead, we simply find a transformation of color space that yields more direct access to shape information. The method is purely local and is able to handle surfaces with arbitrary texture.