Image Data Sets

Color Name Data Sets

For our research on color names we have collected two data sets. To automatically learn color names we collected a set of 100 images for each of the eleven basic color terms: black, blue, brown, grey, green, orange, pink, purple, red, white, and yellow. The images are collected with Google Image by using the color term together with the term "color", so for red the query in Google Image is "red+color".
A tar-file containing 1100 color name labelled images: google_colors.tar

To evaluate color name mappings we have collected a set containing real-world objects accompanied by a color name. The data set contains images collected from EBAY auction site (www.ebay.com). The set contains four classes: cars, shoes, dresses, and pottery. Each class contains 10 images for each of the eleven basic color terms. The color names were assigned to the images by EBAY users. For each image we have hand-segmented the object areas which correspond to the color name
A tar-file containing the ebay images: ebay_data.tar

The data set has been used in the following publication:

J. van de Weijer, C. Schmid, J. Verbeek Learning Color Names from Real-World Images, Proc. CVPR07, Minneapolis, USA, 2007.
J. van de Weijer, C. Schmid, Applying Color Names to Image Description , Proc. ICIP2007, San Antonio, USA, 2007.

Variation in Blur

To test image descriptions with respect to variations of image blur we have collected a data set of 20 image pairs with variations in blur. The changes in blur are caused by relative motion between the camera and the object, and changes in focus of the camera. The images were captured by Matthijs Douze.

Here are some more examples: Blur Image Data
A tar-file containing the 20 image pairs: blur_data.tar

The data set has been used in the following publication:

J. van de Weijer, C. Schmid, Blur Robust and Color Constant Image Description,Proc. ICIP06, Atlanta, 2006.

Soccer Team Data Set

This data set contains images from 7 soccer teams taken from the web, containing 40 images per class, divided into 25 training and 15 testing images per class. Although, players of other teams were allowed to appear in the images, no players being a member of the other classes in the database were allowed.

A tar-file containing the 280 image is available at: soccer_data.tar

The data set has been used in the following publication:

J. van de Weijer, C. Schmid, Coloring Local Feature Extraction, Proc. ECCV2006, Graz, Austria, 2006.
J. van de Weijer, C. Schmid, Applying Color Names to Image Description , Proc. ICIP2007, San Antonio, USA, 2007.