epSICAR: an emerging patterns based approach to sequential, interleaved and concurrent activity recognition

Tao Gu, Zhanqing Wu, Xianping Tao, Hung Keng Pung, Jian Lu

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

150 Citations (Scopus)

Abstract

Recognizing human activities from sensor readings has recently attracted much research interest in pervasive computing. This task is particularly challenging because human activities are often performed in not only a simple (i.e., sequential), but also a complex (i.e., interleaved and concurrent) manner in real life. In this paper, we propose a novel emerging patterns based approach to sequential, interleaved and concurrent activity recognition (epSICAR). We exploit emerging patterns as powerful discriminators to differentiate activities. Different from other learning-based models built upon the training dataset for complex activities, we build our activity models by mining a set of emerging patterns from the sequential activity trace only and apply these models in recognizing sequential, interleaved and concurrent activities. We conduct our empirical studies in a real smart home, and the evaluation results demonstrate that with a time slice of 15 seconds, we achieve an accuracy of 90.96% for sequential activity, 87.98% for interleaved activity and 78.58% for concurrent activity.
Original languageEnglish
Title of host publication2009 IEEE International Conference on Pervasive Computing and Communications (PerCom 2009)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-9
Number of pages9
ISBN (Electronic)9781424433049
DOIs
Publication statusPublished - 2009
Externally publishedYes
EventIEEE International Conference on Pervasive Computing and Communications (7th : 2009)
- Galveston, United States
Duration: 9 Mar 200913 Mar 2009

Conference

ConferenceIEEE International Conference on Pervasive Computing and Communications (7th : 2009)
Abbreviated titlePerCom 2009
CountryUnited States
CityGalveston
Period9/03/0913/03/09

Keywords

  • activity recognition
  • emerging patterns
  • sequential
  • interleaved and concurrent activities
  • wireless sensor networks

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