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Visual Texture: Accurate Material Appearance Measurement, Representation and Modeling Softcover reprint of the original 1st ed. 2013 [Mīkstie vāki]

  • Formāts: Paperback / softback, 284 pages, height x width: 235x155 mm, weight: 5378 g, XXXI, 284 p., 1 Paperback / softback
  • Sērija : Advances in Computer Vision and Pattern Recognition
  • Izdošanas datums: 23-Aug-2016
  • Izdevniecība: Springer London Ltd
  • ISBN-10: 1447169158
  • ISBN-13: 9781447169154
  • Mīkstie vāki
  • Cena: 91,53 €*
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  • Formāts: Paperback / softback, 284 pages, height x width: 235x155 mm, weight: 5378 g, XXXI, 284 p., 1 Paperback / softback
  • Sērija : Advances in Computer Vision and Pattern Recognition
  • Izdošanas datums: 23-Aug-2016
  • Izdevniecība: Springer London Ltd
  • ISBN-10: 1447169158
  • ISBN-13: 9781447169154
This book surveys the state of the art in multidimensional, physically-correct visual texture modeling. The authors review the entire process of texture synthesis, visualization, measurement and analysis, as well as applications in medicine and industry.

This book surveys the state of the art in multidimensional, physically-correct visual texture modeling. Features: reviews the entire process of texture synthesis, including material appearance representation, measurement, analysis, compression, modeling, editing, visualization, and perceptual evaluation; explains the derivation of the most common representations of visual texture, discussing their properties, advantages, and limitations; describes a range of techniques for the measurement of visual texture, including BRDF, SVBRDF, BTF and BSSRDF; investigates the visualization of textural information, from texture mapping and mip-mapping to illumination- and view-dependent data interpolation; examines techniques for perceptual validation and analysis, covering both standard pixel-wise similarity measures and also methods of visual psychophysics; reviews the applications of visual textures, from visual scene analysis in medical applications, to high-quality visualizations in the automotive industry.

Motivation.- Representation.- Texture Acquisition.- Static Multispectral Textures.- Dynamic Textures.- Spatially-Varying Bidirectional Reflectance Distribution Functions.- Bidirectional Texture Functions.- Visualization.- Perceptual Validation and Analysis.- Applications.- Conclusions and Open Problems.

Dr. Michal Haindl is a Professor and Head of the Department of Pattern Recognition at the Institute of Information Theory and Automation within the Academy of Sciences of the Czech Republic. Dr. Jiķ Filip is a Research Associate at the same institution.