Real-time integrated human activity recognition system based on multimodal user understanding

Jun Ho Choi, Kyungmin Kim, Taejin Park, Junho Yun, Jong Hwan Lee, Songkuk Kim, Hyunjung Shim, Jong Seok Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents our real-time human activity recognition system that understands human behavior using multimodal sensor data at multiple levels. Our system consists of a multimodal data acquisition framework and a user understanding algorithm including user identification, activity recognition, and health monitoring components.

Original languageEnglish
Title of host publicationProceedings of the 25th International Conference on Intelligent User Interfaces Companion. IUI 2020
PublisherAssociation for Computing Machinery
Pages89-90
Number of pages2
ISBN (Electronic)9781450375139
DOIs
Publication statusPublished - 2020 Mar 17
Event25th International Conference on Intelligent User Interfaces, IUI 2020 - Cagliari, Italy
Duration: 2020 Mar 172020 Mar 20

Publication series

NameInternational Conference on Intelligent User Interfaces, Proceedings IUI

Conference

Conference25th International Conference on Intelligent User Interfaces, IUI 2020
CountryItaly
CityCagliari
Period20/3/1720/3/20

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction

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  • Cite this

    Choi, J. H., Kim, K., Park, T., Yun, J., Lee, J. H., Kim, S., Shim, H., & Lee, J. S. (2020). Real-time integrated human activity recognition system based on multimodal user understanding. In Proceedings of the 25th International Conference on Intelligent User Interfaces Companion. IUI 2020 (pp. 89-90). (International Conference on Intelligent User Interfaces, Proceedings IUI). Association for Computing Machinery. https://doi.org/10.1145/3379336.3381482