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Camera Calibration
Data from calibration experiments

Synthetic Test Data
For testing colour constancy algorithms

Colour Test Images
For testing colour constancy algorithms

Objects Under Different Lights
For testing colour-based object recognition

Reflectance Spectra of Fluorescent Surfaces

http://www.ensc.sfu.ca/images/trans-bit.gif

  

Data for Computer Vision and Computational Colour Science

 Data Available Online

 

  • Funt et al. HDR Dataset

Link to this dataset

  • Ciurea's Dataset

Ciurea, F. and Funt, B.
" A Large Image Database for Color Constancy Research,"
Proceedings of the Imaging Science and Technology Eleventh Color Imaging Conference, pp. 160-164, Scottsdale, Nov. 2003.

Link to this dataset.

  • Barnard's Datasets

These datasets were gathered as part of Kobus Barnard's Ph.D. research at SFU. Appropriate archival references for the data accompany each dataset.

Camera Calibration Data for Sony DXC-930.
Colour Constancy Synthetic Test Data.
Colour Constancy Test Images Captured Using Sony DXC-930.
Images of Objects Under Different Illuminants.
Spectra of Fluorescent Surfaces.
Object Recognition Image Database (Old Version - 1998)

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The original dataset is described in Peter Gehler and Carsten Rother and Andrew Blake and Tom Minka and Toby Sharp, "Bayesian Color Constancy Revisited", Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2008. The original Gehler dataset is available from here.

We thank Dr. Peter Gehler for making his images publically available and for permission to post our new versions of them. The new SFU Shi version is available for download here. Note that the black level offset needs to be subtracted from the original images. A Matlab template for loading the images and removing the offset is available here.

  • Three Manually Labeled Color Constancy Datasets

Link to this dataset.

Bing Li, Weihua Xiong, Weiming Hu, Brian Funt

May
15, 2012

A total of 1,913 images are included in the 3 data sets. We manually labeled each of these images with its the 3D stages and its indoor/outdoor classification. Following Nedovic et al., the 15 typical 3D stages sky+bkg+grd, bkg+grd, sky+grd, grd, nodepth, grd+Tbkg(LR), grd+Tbkg(RL), Tbkg(LR), Tbkg(RL), tbl+Prs+bkg, 1sd+wall(LR), 1sd+wall(RL), corner, corridor, and prs+bkg are used. There are separate files in both Matlab (.mat) and plain text (.txt) formats containing the file name from the original data set, a 0/1 flag indicating indoor/outdoor, and a numerical stage value.

The image labeling provided here has been used in a paper entitled, “Evaluating Combinational Illumination-Estimation Methods on Real-World Images,” by Bing Li, Weihua Xiong, Weiming Hu, Brian Funt. This paper is still under review (as of May 2012) and is not yet publically available. If you use the label sets we provide here, please contact one of the authors for information on how to cite the database. E-mail addresses are: bli@nlpr.ia.ac.cn,  wallace.xiong@gmail.com, and funt@sfu.ca.

 

  • Metamer Mismatching Hue Circle Transition Wavelengths

 

Full precision data for Table II of “Logvinenko, A.D., Funt, B., and Godau, C., "Metamer Mismatching," IEEE Trans. on Image Processing, Vol. 23, No. 1, pp. 34-43, Jan. 2014” is available here. The data files consist of 20 rows of the 5 transition wavelengths defining a reflectance spectrum. Note that transitions T1, ..., T5 are given in order. In some rows the wavelengths are increasing, some decreasing. For the increasing case, the reflectance is zero for all wavelengths less than T1, one from T1 to T2, zero from T2 to T3, and so on. For the decreasing case, the reflectance is zero for all wavelengths greater than T1, one from T1 down to T2, zero from T2 down to T3, and so forth.

Computational Vision Lab
Computing Science,
Simon Fraser University,
Burnaby, BC, Canada,
V5A 1S6

Fax: (778) 782-3045
Tel: (778) 782-4717
Office: TASC 8005, SFU


Last Updated: May 07, 2014