The dataset contains eyetracking data from 25 observers for 84 uncompressed images from the Berkeley Segmentation Dataset (http://www.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/segbench/). There is no degradation on these images. A text file presents the general conditions of this test. It is a free task experiment.
Database at FTP, no password. Link: ftp://ftp.ivc.polytech.univ-nantes.fr/IRCCyN_IVC_Eyetracker_Berkeley_Database/ Qualinet Databases Mirror: Link: ftpes://multimediatech.cz/IRCCyN_IVC/IRCCyN_IVC_Eyetracker_Berkeley_Database Username: dbq-mirrors Password: kucykepe
The original link was: http://www.irccyn.ec-nantes.fr/spip.php?article554
References and Citation
Please, cite the following paper in your reference if you use this database for your work [WCC10]. Please, cite also the paper from Berkeley for the database [MFM01].
MFM01: D. Martin, C. Fowlkes, D. Tal and J. Malik, "A Database of Human Segmented Natural Images and its Application to Evaluating Segmentation Algorithms and Measuring Ecological Statistics", Proc. 8th Int’l Conf. Computer Vision, Vol. 2, Pages 416-423, July 2001.
WCC10: J. Wang, D. M. Chandler, P. Le Callet, "Quantifying the relationship between visual salience and visual importance", Spie Human and Electronic imaging (HVEI) XV, San Jose, 2010.