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Behavior-Based Emotion Recognition Using Kinect and Hidden Markov Models

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Artificial Intelligence and Soft Computing (ICAISC 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11509))

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Abstract

According to the literature review the autistic children behavior is strictly connected to their emotions. Moreover, it is repeatable and – although it is understandable only for their caregivers – it seems to be predictable. We state a hypothesis supported by the literature’s findings that it should be possible to describe autistic child’s behavior using the statistic models. However, every autistic person is different and therefore the model should be developed individually for each of them. We present a preliminary research on behavior-based emotion recognition and methods for behavior model estimation by using Hidden Markov Models. The behavior model may be created for any combination of following types of events: body positions, activities based on position changes, activities based on hand movements. The conducted experiments provide very satisfactory results. The major conclusion is to use the complex events such as activities.

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Acknowledgment

This work was supported by the statutory funds of the Faculty of Electronics 0401/0140/18, Wroclaw University of Science and Technology, Wroclaw, Poland.

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Correspondence to Aleksandra Postawka .

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Postawka, A. (2019). Behavior-Based Emotion Recognition Using Kinect and Hidden Markov Models. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2019. Lecture Notes in Computer Science(), vol 11509. Springer, Cham. https://doi.org/10.1007/978-3-030-20915-5_23

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  • DOI: https://doi.org/10.1007/978-3-030-20915-5_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20914-8

  • Online ISBN: 978-3-030-20915-5

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