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EmoSens – The Proposal of System for Recognition of Emotion with SDK Affectiva and Various Sensors

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Intelligent Computing Theories and Application (ICIC 2019)

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The face recognition and subject emotion classification is also an important area of current studies in psychology, with many potential uses and applications. Correctly assessing and recognizing subject’s emotion can lead to better understanding its behavior. However the used methods in present often have had a multitude of disadvantages. Therefore, we have set upon creating a solution that is modular and invariant from surrounding light conditions, which in the past represented the biggest problem. We can do so by using an array of data resources (localization of eye pupil) and data from sensors that complement each other, diminishing their disadvantages and reinforcing confidence. These data we can measure using to human physiological properties – pulse (heart rate sensor) and skin response (GSR). To verify of our proposed solution, we realized a simple experiment (displaying the various video clips to 50 participants). This experiment showed that the using SDK Affdex and the particular sensors, we achieved greater classification success rate (90.79%) than with alone SDK Affdex (85.04%).

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This paper was created with the financial support of the projects: 1. Research and Innovation for the project Fake news on the Internet - identification, content analysis, emotions (code: NFP313010T527). 2. The project UGA: Gathering data on understanding of study materials based upon the students’ pupil movement (code: VII/9/2019). 3. The project KEGA 036UKF-4/2019, Adaptation of the learning process using sensor networks and the Internet of Things.

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Correspondence to Martin Magdin .

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Magdin, M., Kohútek, M., Koprda, Š., Balogh, Z. (2019). EmoSens – The Proposal of System for Recognition of Emotion with SDK Affectiva and Various Sensors. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theories and Application. ICIC 2019. Lecture Notes in Computer Science(), vol 11643. Springer, Cham.

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