Action Recognition Through Device Sensors

Jevons Wang, Jiacheng Shang, Jie Wu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We have proposed a new form of action recognition using motion sensors built in mobile and wearable devices. Due to the miniaturization of hardware sensors, action classification through mobile sensors has become a much more attainable task. Using Android and Tizens integrated development environment, we have devised applications for each of these devices to document raw sensor data for analysis. Utilizing dynamic time warping, we attempt to recognize and classify actions based on differences in euclidean distances to build a strong database for further development.

Original languageEnglish
Title of host publicationProceedings - 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages492-496
Number of pages5
ISBN (Electronic)9781538623237
DOIs
StatePublished - 14 Nov 2017
Event14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017 - Orlando, United States
Duration: 22 Oct 201725 Oct 2017

Publication series

NameProceedings - 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017

Conference

Conference14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017
CountryUnited States
CityOrlando
Period22/10/1725/10/17

Keywords

  • action classification
  • action recognition
  • dynamic time warping
  • time series
  • Wearable device

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