Research ->Projects, Publications, Software & Datasets, People Software & Datasets -> Eye Movement Classification Software (offline classification) Eye Movement Classification Software (offline classification) The software contains the implementation of five popular eye movement classification algorithms that allow extraction of fixations and saccades from the recorded raw eye position trace: Velocity Threshold Identification (I-VT), Hidden Markov Model Identification (I-HMM), Dispersion Threshold Identification (I-DT), Minimum Spanning Tree Identification (I-MST), and Kalman Filter Identification (I-KF). The software also contains the algorithms that allow to classify smooth pursuit. These algorithms are Velocity and Velocity Threshold Identification (I-VVT), Velocity and Movement Pattern Identification (I-VMP), Velocity and Dispersion Threshold Identification (I-VDT). The description of the algorithms is presented here [.pdf] Additionally the software computes standardized behavior scores that allow meaningful threshold and input parameters selection for any eye movement classification method. We have decided to make the software available to the eye-tracking research community free of charge. If you use this software in your research to detect fixations, saccades, and smooth pursuits please reference this website and the following articles:
Additional technical report that contains the description of the pseudo-code for each algorithm can be found here. Download software here. If you download the software it is assumed that you agree to the copyright agreement at the bottom of the page. The compressed files have been password protected. Please email Dr. Oleg Komogortsev for the password. Kindly indicate your university/industry affiliation and a brief description of how you plan to use the software. Please use words "eye movement classification software" in the subject line. Acknowledgment: special thanks are expressed to Dr. Alex Karpov for the code development, optimizations, bug fixes, and GUI included in the software. Currently this project is funded in part by the NSF CAREER award #CNS-1250718, in part by the #60NANB12D234 grant from the National Institute of Standards and funds from Texas State University. In the past this project was funded in part by the grant #60NANB10D213 from the National Institute of Standards. COPYRIGHT NOTICE STARTS HERE-------------------------------------------------------------- Copyright
© 2014 The Texas State University Permission is hereby granted, without written agreement and without license or royalty fees, to use, copy, modify, and distribute this software and its documentation for any purpose, provided that the copyright notice in its entirety appear in all copies of this software, and the original source of this software, Human Computer Interaction Laboratory at the Texas State University, is acknowledged in any publication that reports research using this software. The software is to be cited in the bibliography as:
IN NO EVENT SHALL THE TEXAS STATE UNIVERSITY BE LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE TEXAS STATE UNIVERSITY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE TEXAS STATE UNIVERSITY SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED ON AN "AS IS" BASIS, AND THE TEXAS STATE UNIVERSITY HAS NO OBLIGATION TO PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. COPYRIGHT NOTICE ENDS HERE----------------------------------------------------------------- |
|