Scanpath Classification - SubsMatch 2.0
Our eye movements are driven by a continuous trade-off between the need for detailed examination of objects of interest and the necessity to keep an overview of our surrounding. In consequence, behavioral patterns that are characteristic for our actions and their planning are typically manifested in the way we move our eyes to interact with our environment. Identifying such patterns from individual eye movement measurements is however highly challenging.
SubsMatch 2.0 tackles the challenge of quantifying the influence of experimental factors on eye movement sequences. It can extract sequence-sensitive features from eye movements and classify eye movements sequences based on the frequencies of small subsequences.
Our results show that the proposed method is able to classify eye movement sequences over a variety of experimental designs.
Note: As external programs are utilized, we cannot ship a ready-to-use program but you have to run the bootstrap-script yourself. It will download and install all the necessary programs as well as the data. See the README for details.
T.C. K├╝bler, C. Rothe, U. Schiefer, W. Rosenstiel, E. Kasneci (2016). SubsMatch 2.0: Scanpath comparison and classification based on subsequence frequencies. Behavior Research Methods, (to appear 2016)
Scanpath Comparison - SubsMatch
SubsMatch is a scanpath comparison tool designed specifically for dynamic scenarios. It is based on a string alignment metric. Fixations are translated to a letter representation based on their location and assigned to equiprobabilistic bins.
Distance calculation is performed on the frequencies of subsequences.
The Matlab implementation together with an evaluation dataset of patients with visual field defects driving in a driving simulator is available here: www-ti.informatik.uni-tuebingen.de/~kueblert/SubsMatch1.0.zip
T. C. K├╝bler, E. Kasneci, W. Rosenstiel (2014). SubsMatch: Scanpath Similarity in Dynamic Scenes based on Subsequence Frequencies. Proceedings of the 8th Symposium on Eye Tracking Research and Applications (ETRA 2014)
SubsMatch was applied to gaze movements of microneurosurgeons during a Tumor removal surgery in order to determine surgeon Expertise based on gaze behavior.
The distance matrix of pairwise scanpath comparisons shows expertise clusters, where scanpath distances between expert surgeons are quite small and distances between an expert and a novice are rather large. This suggests a separability of the groups.
Scanning Patterns with highest occurrence frequency difference between the groups reveal that expert surgeons exhibit highly repetitive scanning only at the very beginning of Stimulus presentation while novices continue the pattern.
T.C. K├╝bler, S. Eivazi, E. Kasneci (2015). Automated Visual Scanpath Analysis Reveals the Expertise Level of Micro-neurosurgeons. MICCAIÔÇÖ15 Workshop on Interventional Microscopy