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

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) Shi's Re-processed Version of the Gehler Color Constancy Dataset of 568 Images This dataset is based on work done by Dr. Lilong Shi at Simon Fraser University with Dr. Brian Funt. It involves processing the original RAW format images provided by Gehler et al. to generate a new set of high quality linear images. New ground truth illumination measurements are also provided for these images. 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. 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.