reflectance and texture of real-world surfaces kristin j. dana columbia university bram van ginneken...

Reflectance and Texture of Real-World Surfaces

KRISTIN J. DANAColumbia University

BRAM VAN GINNEKENUtrecht UniversitySHREE K. NAYAR

Columbia UniversityJAN J. KOENDERINK

Utrecht University

ACM Transactions on Graphics, Vol. 18, No. 1, January 1999

Overview

• Introduce BRDF and BTF

• BTF Texture Gathering Technique

• CUReT Database

• BTF Applications

• Future Work

• Pretty Pictures

Bidirectional Reflectance Distribution Function (BRDF)

• Nicodemus [1970] and Nicodemus et al. [1977]

• Coarse scale level– local surface variations are

subpixel– local intensity is uniform

• Bidirectional:1. Camera Angle2. Light Angle

• “Objects look differently when viewed from different angles, and when illuminated from different directions”

Bidirectional Texture Function (BTF)

• Fine scale level– Surface variations give rise to local intensity

variations

• Bidirectional:1.Camera Angle

2.Light Angle

• “Objects look differently when viewed from different angles, and when illuminated from different directions”

BRDF vs. BTF

Why do we need BTFs?• Traditional 2-D texture synthesis and texture-mapping do not take into account the

change in texture appearance as the viewing and illumination directions change– A single digital image of a rough surface is mapped onto a 3-D object and the

appearance of roughness is usually lost or distorted• Bump-mapping [Blinn 1977, 1978] preserves some of the appearance of

roughness– knowledge of the surface shape is required– shadows cast from the local surface relief are not rendered

• ray tracing can be used– exact geometry of the surface must be known– high computational cost

• solid texturing: combine a volumetric texture synthesis with volume rendering techniques

– computationally intensive– applicable for a limited variety of textures.

• BTF database– “potential exists for 3-D texturing algorithms using images, without the need for a

volumetric texture model or surface synthesis procedure”

BTF: Where do we start?• Already BRDF databases

• Employ new techniques to create BTF database

• Pull Together:– Robot– Lamp– PC– Photometer– Video camera

Texture Gathering Technique

• Fixed light source– Halogen bulb with a Fresnel lens (single-

beam focusing)

• Camera moves through 7 positions– 22.5°, 45°, 67.5°, 90°, 112.5°, 135°, 157.5°

from light source

• Texture sample moves through multiple orientations– Robot arm orients sample normal along

vertices of quarter-sphere facing the light source


• At each camera position, texture is captured with its normal along quarter-sphere vertices

• Not all vertices captured at each position– At position 7, only a few

normals are actually visible to the camera

Quarter-Sphere Orientations: Camera Positions


• Sample lies in xs–ys plane with its global normal pointing in the direction of zs

• Each circular marker represents a distinct illumination direction

• For each of these illumination directions, the sample is imaged from seven viewing directions

Quarter-Sphere Orientations: Illumination Directions


• Textures that have grids or grains

• Measurements are repeated rotating sample about zs by either 45° or 90° depending on the structure of the anisotropy

• Examples: – Linen (square grid)

rotated 45°– Corduroy (vertical lines)

rotated 90 °

Special Case: Anisotropic Textures


• Relate radiance to pixel values• Use Kodak standard card

image for every sample measured.

• Letting r denote the total radiance and p denote the average pixel value, a linear relationship was found

• Data with significant pixel underflow (pixel values near 0) or overflow (pixel values near 255) were not used.

Control Considerations

End Product

• 205 images for each sample

• 640 x 480 pixels• 24 bits per pixel (8 bits per

RGB channel).• Database total: over

14,000 images (61 samples, 205 measurements per sample, plus 205 additional measurements for anisotropic samples)

• CUReT Database:www.cs.columbia.edu/CAVE/curet/

Camera Position Images

1 55

2 48

3 39

4 28

5 19

6 12

7 4

Total 205

Columbia-Utrecht Reflectance and Texture Database (CUReT)

BTF Applications

• Top row– Two images of “plaster_b” with

different illumination and viewing directions

• Bottom row– Spatial spectrum of “plaster_b” with

zero frequency at the center and brighter regions corresponding to higher magnitudes

– Notice orientation change due to change of illumination direction causing change in shadow direction.

• Computer vision:– Texture recognition algorithms often

based on spectral content of image textures

– BTF should be considered for recognition of real-world surfaces

Sample 11: “plaster_b”

BTF Applications• BTF texture gathering

technique allows easy gathering of BRDF data– Pros:

• Simple system• Simultaneously gather

BRDF and BTF measurements

– Cons:• Not as accurate as

traditional BRDF measurement systems

Future Work

Synthesizing Bidirectional Texture Functions for Real-World Surfaces

Xinguo Liu, Yizhou Yu, Heung-Yeung Shum• 3 Step approach to synthetically generate BTFs

1. Recovers approximate 3D geometry of surface details using a shape-from-shading approach

2. Generates a novel version of the geometric details with the same statistical properties as the sample surface

3. Uses an “appearance preserving procedure” to synthesize novel images under various viewing/lighting settings, defining a novel BTF

Show me some BTF pictures!!!

• 13 images per sample used from database collection of 205– 1 image of frontal view– 12 oblique views

• Use averaging of three pixels at the section borders to reduce the appearance of seams

Pretty Pictures

Traditional2-D texture-mapping

BTF3-D texture-mapping

Sample 11 (plaster)

Pretty Pictures



Sample 8 (pebbles)

Pretty Pictures



Sample 45 (concrete)

Pretty Pictures



Sample 28 (crumpled paper)

Pretty Pictures



Sample 19 (plush rug)

Pretty Pictures



Sample 56 (wood) (anisotropic)

reflectance and texture of real-world surfaces kristin j. dana columbia university bram van ginneken...

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