Abstract
The paper presents studies on the application of the dissimilarity matrix-based method to the eye movement analysis. This method was utilized in the biometric identification task. To assess its efficiency four different datasets based on similar scenario (‘jumping point’ type) yet using different eye trackers, recording frequencies and time intervals have been used. It allowed to build the common platform for the research and to draw some interesting comparisons. The dissimilarity matrix, which has never been used for identifying people on the basis of their eye movements, was constructed with usage of different distance measures. Additionally, there were different signal transforms and metrics checked and their performance on various datasets was compared. It is worth mentioning that the paper presents the algorithm that was used during the BioEye 2015 competition and ranked as one of the top three methods.
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Acknowledgments
The authors would like to thank organizers of BioEye 2015 competition for publishing eye movement datasets that were used in this research. We also acknowledge the support of Silesian University of Technology grant BK/263/RAu2/2016.
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Kasprowski, P., Harezlak, K. (2016). Using Dissimilarity Matrix for Eye Movement Biometrics with a Jumping Point Experiment. In: Czarnowski, I., Caballero, A.M., Howlett, R.J., Jain, L.C. (eds) Intelligent Decision Technologies 2016. Smart Innovation, Systems and Technologies, vol 57. Springer, Cham. https://doi.org/10.1007/978-3-319-39627-9_8
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DOI: https://doi.org/10.1007/978-3-319-39627-9_8
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