The Scale of Geometric Texture

  • Geoffrey Oxholm
  • Prabin Bariya
  • Ko Nishino
Conference paper

DOI: 10.1007/978-3-642-33718-5_5

Volume 7572 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Oxholm G., Bariya P., Nishino K. (2012) The Scale of Geometric Texture. In: Fitzgibbon A., Lazebnik S., Perona P., Sato Y., Schmid C. (eds) Computer Vision – ECCV 2012. ECCV 2012. Lecture Notes in Computer Science, vol 7572. Springer, Berlin, Heidelberg

Abstract

The most defining characteristic of texture is its underlying geometry. Although the appearance of texture is as dynamic as its illumination and viewing conditions, its geometry remains constant. In this work, we study the fundamental characteristic properties of texture geometry—self similarity and scale variability—and exploit them to perform surface normal estimation, and geometric texture classification. Textures, whether they are regular or stochastic, exhibit some form of repetition in their underlying geometry. We use this property to derive a photometric stereo method uniquely tailored to utilize the redundancy in geometric texture. Using basic observations about the scale variability of texture geometry, we derive a compact, rotation invariant, scale-space representation of geometric texture. To evaluate this representation we introduce an extensive new texture database that contains multiple distances as well as in-plane and out-of plane rotations. The high accuracy of the classification results indicate the descriptive yet compact nature of our texture representation, and demonstrates the importance of geometric texture analysis, pointing the way towards improvements in appearance modeling and synthesis.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Geoffrey Oxholm
    • 1
  • Prabin Bariya
    • 1
  • Ko Nishino
    • 1
  1. 1.Department of Computer ScienceDrexel UniversityPhiladelphiaUSA