Scanpath Comparison for Visual Search Analysis

Eye Tracking | Classification | Art


Users are given a visual task, while I study their scanpaths. Scanpaths are sequences of eye movements. After recording the scanpaths with an eye tracker, I want to analyze the recorded data; and my research question was: It is possible to classify users into different groups only by using scanpaths?


I took a concrete example: Given scanpath from art experts and laymen looking at famous paintings, I tried to classify them according to their expertise. After temporal binning, feature discretization, binary representation, data reshaping, and dimensionality reduction, I could classify viewers with an accuracy of 64.64%. Interestingly, I also found that a user’s scanpath is characteristic for that user, i.e., the user can be recognized among others, so a user seems to have a particular fingerprint.

My Role

This was my master thesis ; it was a cooperation of HPI with the Computer Engineering Department of University of Tuebingen. I had the opportunity to apply techniques from Machine Learning and Data Mining, techniques that had not been used for this before.


MATLAB, Graphical Models, Hidden Markov Models, SVD, Data Cleansing, R

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