Material Appearance Modeling : A Data-Coherent Approach
By: Dong, Yue.
Contributor(s): Lin, Stephen | Guo, Baining.Material type: TextSeries: eBooks on Demand.Publisher: Dordrecht : Springer, 2013Description: 1 online resource (182 p.).ISBN: 9783642357770.Subject(s): Computer graphics | Computer vision | Image processing -- Digital techniquesGenre/Form: Electronic books.Additional physical formats: Print version:: Material Appearance Modeling : A Data-Coherent ApproachDDC classification: 006.6 Online resources: Click here to view this ebook.
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Material Appearance Modeling: A Data-Coherent Approach; Preface; Contents; Chapter 1: Introduction; 1.1 Background; 1.1.1 Fundamentals of Light Interaction with Materials; 1.1.2 Taxonomy of Light Scattering Functions; 1.1.3 Modeling and Rendering Pipeline of Material Appearance; 1.2 Data Coherence for Appearance Modeling; 1.2.1 Data Coherence; 1.2.2 Coherence-Based Reconstruction; 1.2.3 A General Framework for Coherence-Based Appearance Modeling; 1.3 Overview; 1.3.1 Acquisition and Modeling of Opaque Surfaces; 1.3.2 Modeling and Rendering of Subsurface Light Transport
1.3.3 Material FabricationReferences; Part I: Acquisition and Modeling of Opaque Surfaces; Chapter 2: Surface Reﬂectance Overview; 2.1 Surface Reﬂectance Acquisition; 2.1.1 Direct Measurement; 2.1.2 Angular Coherence; 2.1.3 Spatial Coherence; 2.2 Interactive Modeling and Editing; References; Chapter 3: Efﬁcient SVBRDF Acquisition with Manifold Bootstrapping; 3.1 Related Work; 3.2 SVBRDF Manifold Bootstrapping; 3.2.1 Representative and Key Measurement; Representative Measurement; Key Measurement; 3.2.2 Manifold Bootstrapping Overview; Local BRDF Reconstruction
Representative Projection and Bootstrapping3.2.3 Manifold Bootstrapping Details; Estimating Local BRDF Dimensionality; Uniform Measurement Scaling; Neighborhood Selection; Local Linear Combination; 3.2.4 Synthetic Enlargement for Representatives; 3.2.5 Key Measurement Validation; 3.3 SVBRDF Data Acquisition; 3.3.1 Acquiring Representatives: BRDF Samples; Device Setup; Calibration; Capturing; Reconstruction; 3.3.2 Acquiring Keys: Reﬂectance Maps; Key Lighting Dimensionality; Key Lighting Size; 3.4 Experimental Results; 3.4.1 Method Validation; Test on Fully-Sampled SVBRDF
Comparison with Microfacet SynthesisEffect of Neighborhood Size; 3.4.2 SVBRDF Capture Results; 3.5 Conclusion; References; Chapter 4: Interactive SVBRDF Modeling from a Single Image; 4.1 Related Work; 4.2 System Overview; 4.3 User-Assisted Shading Separation; 4.3.1 Separation as Optimization; 4.3.2 Interactive Reﬁnement; User Strokes; Result Reﬁnement; 4.3.3 Discussion; 4.4 Two-Scale Normal Reconstruction; Discussion; 4.5 User-Assisted Specular Assignment; Material Classiﬁcation; Specular Coefﬁcient Assignment; 4.6 Experimental Results; Performance; User Input
Comparison with Standard ToolsetsResults; Limitations; 4.7 Conclusion; References; Part II: Modeling and Rendering of Subsurface Light Transport; Chapter 5: Overview of Subsurface Light Transport; 5.1 Computing Subsurface Light Transport; 5.2 Capturing Subsurface Scattering Effects; References; Chapter 6: Modeling Subsurface Light Transport with the Kernel Nyström Method; 6.1 Related Work; 6.2 The Kernel Nyström Method; 6.2.1 Kernel Extension; 6.2.2 Estimating the Light Transport Kernel f; 6.3 Adaptive Light Transport Measurement; Device Setup and Calibration; Column Sampling
6.4 Results and Discussions
A principal aim of computer graphics is to generate images that look as real as photographs. Realistic computer graphics imagery has however proven to be quite challenging to produce, since the appearance of materials arises from complicated physical processes that are difficult to analytically model and simulate, and image-based modeling of real material samples is often impractical due to the high-dimensional space of appearance data that needs to be acquired.This book presents a general framework based on the inherent coherency in the appearance data of materials to make image-based appeara
Description based upon print version of record.