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Conference Paper Intelligent Interaction System Capable of Autonomous Mobility for At-Home Workouts
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Authors
Samyeul Noh, Sang-baek Lee, Jiyoung Park
Issue Date
2019-10
Citation
International Conference on Information and Communication Technology Convergence (ICTC) 2019, pp.653-657
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICTC46691.2019.8939887
Abstract
In this paper, we present an intelligent interaction system capable of autonomous mobility for at-home workouts. Whereas the current interaction systems for at-home workouts have had much difficulty in mobility, the presented system is able not only to assist people to work out at-home through the use of advanced deep learning technologies such as action recognition, human pose estimation, and bio-signal recognition but also to have autonomous mobility through the utilization of a mobile robot. To verify the system's feasibility with regard to intelligent interaction capable of autonomous mobility, we have conducted individual experiments for each module in the system such as mobile robot navigation, interfacing, unity contents visualization, action recognition, human pose estimation, bio-signal recognition, and human data generation.
KSP Keywords
Action recognition, Data generation, Human Pose estimation, Human data, Intelligent interaction, Interaction System, Learning Technology, Mobile Robot Navigation, bio-signal, deep learning(DL), signal recognition