Personality gaze patterns unveiled via automatic relevance determination

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Abstract

Understanding human gaze behaviour in social context, as along a face-to-face interaction, remains an open research issue which is strictly related to personality traits. In the effort to bridge the gap between available data and models, typical approaches focus on the analysis of spatial and temporal preferences of gaze deployment over specific regions of the observed face, while adopting classic statistical methods. In this note we propose a different analysis perspective based on novel data-mining techniques and a probabilistic classification method that relies on Gaussian Processes exploiting Automatic Relevance Determination (ARD) kernel. Preliminary results obtained on a publicly available dataset are provided.

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Cuculo, V., D’Amelio, A., Lanzarotti, R., & Boccignone, G. (2018). Personality gaze patterns unveiled via automatic relevance determination. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11176 LNCS, pp. 171–184). Springer Verlag. https://doi.org/10.1007/978-3-030-04771-9_14

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