Paper/tissueWoodConcreteWood

Added: April 1, 2013, 8:11 p.m.

FOV: 89.037° (larger dimension)

Focal length: 0.768 × height

Scene: hallway

Scene correct: True

Whitebalanced: True


Scene label correct votes:

4
1

Scene label correct score:

0.252

Whitebalance votes:

4
1

Whitebalance score:

0.215

Flickr user: alex_kuehni

Flickr ID: 7916883920

License: Attribution 2.0 Generic (Credit: Alex K├╝hni)

Material segmentations

Users were asked to draw around regions of a single type of material.

Vanishing points

Each color corresponds to one vanishing point. Hover over the points on the right to see the full lines.

Whitebalance points

Users were asked to click on points that are white or gray.

Each color corresponds to one user.

Median chroma
  • 2.907 (16.6 s)
  • 15.363 (10.7 s)
  • 10.088 (6.14 s)
  • 1.251 (5.35 s)
  • 1.190 (4.26 s)

Human reflectance judgements

Our user interface for collecting annotations shows the user an image and asks them, for a particular pair of pixels (indicated with crosshairs and labeled Points 1 and 2), which of the two points has a darker surface color. The user can then select one of three options: Point 1, Point 2, and About the same. We ask users to specify their confidence in their assessment as Guessing, Probably, or Definitely, as was done by [Branson et al. 2010].

We aggregate judgements from 5 users for each pair of points and use the CUBAM machine learning model [Welinder et al. 2010] to model two forms of bias.

See our publication for more details.

Our user interface

Point separation: 0.07


Intrinsic image decompositions

The input image is decomposed into a "reflectance" and "shading" layer. Note that the reflectance layer is listed twice: color (left) and grayscale (center). Decompositions are ordered by error and then runtime (best on top). The parameters for each algorithm are the same for all photos; they are set to the values that produce lowest mean error (WHDR) for all photos. See our publication for more details.

  • Algorithm: grosse2009_color_retinex

    Reflectance

    Grayscale Reflectance

    Shading

    Citation:

    Roger Grosse, Micah K. Johnson, Edward H. Adelson, William T. Freeman. "Ground truth dataset and baseline evaluations for intrinsic image algorithms". Proceedings of the International Conference on Computer Vision (ICCV). http://www.cs.toronto.edu/~rgrosse/intrinsic/.

    Parameters:

    • L1: True
    • threshold color: 0.7
    • threshold gray: 0.5

    Result:

    • Weighted human disagreement rate (WHDR): 22.9% (δ: 0.1)
    • WHDR for equal edges only: 0.2968
    • WHDR for inequalities only: 0.1697
    • Runtime: 179.1 s

  • Algorithm: grosse2009_grayscale_retinex

    Reflectance

    Grayscale Reflectance

    Shading

    Citation:

    Roger Grosse, Micah K. Johnson, Edward H. Adelson, William T. Freeman. "Ground truth dataset and baseline evaluations for intrinsic image algorithms". Proceedings of the International Conference on Computer Vision (ICCV). http://www.cs.toronto.edu/~rgrosse/intrinsic/.

    Parameters:

    • L1: True
    • threshold: 0.5

    Result:

    • Weighted human disagreement rate (WHDR): 24.1% (δ: 0.1)
    • WHDR for equal edges only: 0.3023
    • WHDR for inequalities only: 0.1873
    • Runtime: 149.4 s

  • Algorithm: bell2014_densecrf

    Reflectance

    Grayscale Reflectance

    Shading

    Citation:

    Sean Bell, Kavita Bala, Noah Snavely. "Intrinsic Images in the Wild". ACM Transactions on Graphics (SIGGRAPH 2014). http://intrinsic.cs.cornell.edu.

    Parameters:

    • abs reflectance weight: 0
    • abs shading gray point: 0.5
    • abs shading weight: 500.0
    • chromaticity weight: 0
    • kmeans intensity scale: 0.5
    • kmeans n clusters: 20
    • n iters: 25
    • pairwise intensity chromaticity: True
    • pairwise weight: 104
    • shading blur init method: none
    • shading blur sigma: 0.1
    • shading target norm: L2
    • shading target weight: 20000.0
    • split clusters: True
    • theta c: 0.025
    • theta l: 0.1
    • theta p: 0.1

    Result:

    • Weighted human disagreement rate (WHDR): 31.7% (δ: 0.1)
    • WHDR for equal edges only: 0.2659
    • WHDR for inequalities only: 0.3615
    • Runtime: 249.6 s

  • Algorithm: garces2012_clustering

    Reflectance

    Grayscale Reflectance

    Shading

    Citation:

    Elena Garces, Adolfo Munoz, Jorge Lopez-Moreno, Diego Gutierrez. "Intrinsic Images by Clustering". Computer Graphics Forum (Eurographics Symposium on Rendering). http://www-sop.inria.fr/reves/Basilic/2012/GMLG12/.

    Parameters:

    • km k: 8
    • remap gamma 2 2: False

    Result:

    • Weighted human disagreement rate (WHDR): 37.2% (δ: 0.1)
    • WHDR for equal edges only: 0.3337
    • WHDR for inequalities only: 0.4053
    • Runtime: 6.0 s

  • Algorithm: zhao2012_nonlocal

    Reflectance

    Grayscale Reflectance

    Shading

    Citation:

    Qi Zhao, Ping Tan, Qiang Dai, Li Shen, Enhua Wu, Stephen Lin. "A Closed-form Solution to Retinex with Non-local Texture Constraints". IEEE Transaction on Pattern Analysis and Machine Intelligence (TPAMI). http://www.ece.nus.edu.sg/stfpage/eletp/Papers/pami12_intrinsic.pdf.

    Parameters:

    • chrom thresh: 0.001
    • gamma: False
    • texture patch distance: 0.0003
    • texture patch variance: 0.03

    Result:

    • Weighted human disagreement rate (WHDR): 37.4% (δ: 0.1)
    • WHDR for equal edges only: 0.0309
    • WHDR for inequalities only: 0.6740
    • Runtime: 26.6 s

  • Algorithm: shen2011_optimization

    Reflectance

    Grayscale Reflectance

    Shading

    Citation:

    Jianbing Shen, Xiaoshan Yang, Yunde Jia, Xuelong Li. "Intrinsic Images Using Optimization". Proceedings of Computer Vision and Pattern Recognition (CVPR). http://cs.bit.edu.cn/~shenjianbing/cvpr11.htm.

    Parameters:

    • rho: 1.9
    • unmap srgb: False
    • wd: 3

    Result:

    • Weighted human disagreement rate (WHDR): 39.1% (δ: 0.1)
    • WHDR for equal edges only: 0.3893
    • WHDR for inequalities only: 0.3920
    • Runtime: 293.7 s

  • Algorithm: baseline_shading

    Reflectance

    Grayscale Reflectance

    Shading

    Parameters: None

    Result:

    • Weighted human disagreement rate (WHDR): 46.1% (δ: 0.1)
    • WHDR for equal edges only: 0.9419
    • WHDR for inequalities only: 0.0399
    • Runtime: 0.1 s

  • Algorithm: baseline_reflectance

    Reflectance

    Grayscale Reflectance

    Shading

    Parameters: None

    Result:

    • Weighted human disagreement rate (WHDR): 53.3% (δ: 0.1)
    • WHDR for equal edges only: 0.0000
    • WHDR for inequalities only: 1.0000
    • Runtime: 0.0 s