Unsupervised activity recognition with user's physical characteristics data

Takuya Maekawa*, Shinji Watanabe

*この研究の対応する著者

研究成果: Conference contribution

66 被引用数 (Scopus)

抄録

This paper proposes an activity recognition method that models an end user's activities without using any la-beled/unlabeled acceleration sensor data obtained from the user. Our method employs information about the end user's physical characteristics such as height and gender to find other users whose sensor data prepared in advance may be similar to those of the end user. Then, we model the end user's activities by using the labeled sensor data from the similar users. Therefore, our method does not require the end user to collect and label her training sensor data. We confirmed the effectiveness of our method by using 100 hours of sensor data obtained from 40 participants, and achieved a good recognition accuracy almost identical to that of a recognition method employing an end user's labeled training data.

本文言語English
ホスト出版物のタイトルProceedings - 15th Annual International Symposium on Wearable Computers, ISWC 2011
ページ89-96
ページ数8
DOI
出版ステータスPublished - 2011 8月 29
外部発表はい
イベント15th Annual International Symposium on Wearable Computers, ISWC 2011 - San Francisco, CA, United States
継続期間: 2011 6月 122011 6月 15

出版物シリーズ

名前Proceedings - International Symposium on Wearable Computers, ISWC
ISSN(印刷版)1550-4816

Other

Other15th Annual International Symposium on Wearable Computers, ISWC 2011
国/地域United States
CitySan Francisco, CA
Period11/6/1211/6/15

ASJC Scopus subject areas

  • ソフトウェア
  • ハードウェアとアーキテクチャ
  • コンピュータ ネットワークおよび通信

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