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Image preference is a subjective factor which plays an important role in Quality-of-Experience (QoE) modelling. Traditionally, preference characterization has been quantified via questionnaires or subjective evaluations. Current advances in neurophysiological signal acquisition, however, have allowed for such “non-measurable” subjective parameters to be quantified objectively. In this pilot study, we explore the use of neurophysiological signals as correlates of image preference characterization. Experiments with seven participants have shown promising results and mental states associated with preferred and non-preferred images, as well as baseline neutral state could be classified with above-chance levels.
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Falk et al. (2012) studied this question.
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