Embracenet for activity: A deep multimodal fusion architecture for activity recognition

Jun Ho Choi, Jong Seok Lee

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

Abstract

Human activity recognition using multiple sensors is a challenging but promising task in recent decades. In this paper, we propose a deep multimodal fusion model for activity recognition based on the recently proposed feature fusion architecture named EmbraceNet. Our model processes each sensor data independently, combines the features with the EmbraceNet architecture, and post-processes the fused feature to predict the activity. In addition, we propose additional processes to boost the performance of our model. We submit the results obtained from our proposed model to the SHL recognition challenge with the team name “Yonsei-MCML.

Original languageEnglish
Title of host publicationUbiComp/ISWC 2019- - Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers
PublisherAssociation for Computing Machinery, Inc
Pages693-698
Number of pages6
ISBN (Electronic)9781450368698
DOIs
Publication statusPublished - 2019 Sep 9
Event2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and 2019 ACM International Symposium on Wearable Computers, UbiComp/ISWC 2019 - London, United Kingdom
Duration: 2019 Sep 92019 Sep 13

Publication series

NameUbiComp/ISWC 2019- - Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers

Conference

Conference2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and 2019 ACM International Symposium on Wearable Computers, UbiComp/ISWC 2019
CountryUnited Kingdom
CityLondon
Period19/9/919/9/13

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

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    Choi, J. H., & Lee, J. S. (2019). Embracenet for activity: A deep multimodal fusion architecture for activity recognition. In UbiComp/ISWC 2019- - Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers (pp. 693-698). (UbiComp/ISWC 2019- - Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers). Association for Computing Machinery, Inc. https://doi.org/10.1145/3341162.3344871