Abstract
This paper discusses the modeling for interactions between the behaviors of participants in a meeting for decision making. First, we adopt the behaviors (i.e., eye, facial, and hand movements) detected by OpenPose [9] as a skeleton detection algorithm using a single camera. Second, we propose a modeling method for the participant behaviors based on neural networks. Furthermore, we discuss the relationships between the participant behaviors and the model parameters in multi-layered neural networks based on the experimental results. Notably, we show that the participant characteristics are represented by the indices based on the parameters of the abovementioned models.
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Acknowledgements
This work was supported by JSPS KAKENHI Grant Number JP19K12261 and JP19K03095.
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Watanabe, E., Ozeki, T., Kohama, T. (2020). Modeling the Behaviors of Participants in Meetings for Decision Making Using OpenPose. In: Auer, M., Hortsch, H., Sethakul, P. (eds) The Impact of the 4th Industrial Revolution on Engineering Education. ICL 2019. Advances in Intelligent Systems and Computing, vol 1134. Springer, Cham. https://doi.org/10.1007/978-3-030-40274-7_3
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DOI: https://doi.org/10.1007/978-3-030-40274-7_3
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