Image-Based Reconstruction of Spatially Varying Materials
Proceedings of the 12th Eurographics Workshop on Rendering Techniques
Example-Based Photometric Stereo: Shape Reconstruction with General, Varying BRDFs
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part IV
Principles of Appearance Acquisition and Representation
Foundations and Trends® in Computer Graphics and Vision
Shape and Spatially-Varying BRDFs from Photometric Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
ACM SIGGRAPH 2011 papers
A Multi-camera, Multi-projector Super-Resolution Framework for Structured Light
3DIMPVT '11 Proceedings of the 2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission
A novel hemispherical basis for accurate and efficient rendering
EGSR'04 Proceedings of the Fifteenth Eurographics conference on Rendering Techniques
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Image-based capture of material appearance has been extensively studied, but the quality of the results and generality of the applied methods leave a lot of room for improvement. Most existing methods rely on parametric models of reflectance and require complex hardware systems or accurate geometric models that are not always available or practical. Rather than independently estimating reflectance properties for each surface point, it is common to express the reflectance as a combination of base materials inherent to each particular object or scene. We propose a method for efficient and automatic extraction of base materials in a photometric stereo system. After jointly estimating per-pixel reflectances and refined surface normals using these materials, we can render photo-realistic images of complex objects under novel lighting conditions in real time.