Understanding visual attention in 3DTV is essential for many applications, e.g., capture, coding, visual confort enhancement, 2D-to-3D conversion, retargeting, and subtitling. Therefore, public datasets of 3D content with associated ground truth eye tracking data are needed. To overcome the lack of publicly available 3D video eye tracking datasets, we created the EyeC3D dataset. Eight stereoscopic video sequences were used in the eye tracking experiments. For each video, eye movement data was recorded via a set of subjective experiments. From the eye movement data, the fixation density maps (FDMs) were computed for each frame of the stereoscopic video sequences. Eight stereoscopic video sequences were used in the eye tracking experiments. Five sequences (Boxers, Hall, Lab, News report, and Phone call) were obtained from the NAMA3DS1 database. Two sequences (Musicians and Poker) were obtained from the European FP7 Research Project MUSCADE. Sequence Poznan Hall2 was obtained from the Poznan multiview video database.
You can download all lists of fixation points and fixation density maps from the following FTP (please use dedicated FTP clients, such as FileZilla or FireFTP): Coming soon!
LicensePermission is hereby granted, without written agreement and without license or royalty fees, to use, copy, modify, and distribute the data provided and its documentation for research purpose only. The data provided may not be commercially distributed. In no event shall the Ecole Polytechnique Fédérale de Lausanne (EPFL) be liable to any party for direct, indirect, special, incidental, or consequential damages arising out of the use of the data and its documentation. The Ecole Polytechnique Fédérale de Lausanne (EPFL) specifically disclaims any warranties. The data provided hereunder is on an "as is" basis and the Ecole Polytechnique Fédérale de Lausanne (EPFL) has no obligation to provide maintenance, support, updates, enhancements, or modifications.
References and Citation
If you use the EyeC3D dataset in your research, we kindly ask you to reference the following paper [HE14] and URL link of this website (http://mmspg.epfl.ch/eyec3d).
HE14: P. Hanhart and T. Ebrahimi. EyeC3D: 3D video eye tracking dataset. Sixth International Workshop on Quality of Multimedia Experience (QoMEX), Singapore, September 2014.