Alexis Narvaez

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This paper presents the construction of a multimodal dataset for deception detection, including physiological, thermal, and visual responses of human subjects under three deceptive scenarios. We present the experimental protocol, as well as the data acquisition process. To evaluate the usefulness of the dataset for the task of deception detection, we(More)
In this paper, we explore a thermal imaging approach to sensing affective state. Using features extracted from a thermal map of the face, obtained from a dataset consisting of 70 recordings of positive, negative, or neutral states, we show that we can effectively predict the presence of affect, with an error reduction of up to 50% as compared to a majority(More)
In this paper, we explore a multimodal approach to sensing affective state during exposure to visual narratives. Using four different modalities, consisting of visual facial behaviors, thermal imaging, heart rate measurements, and verbal descriptions, we show that we can effectively predict changes in human affect. Our experiments show that these modalities(More)
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