From Virtual to Real World: Applying Animation to Design the Activity Recognition System

Chengshuo Xia, Yuta Sugiura

研究成果: Conference contribution

抄録

Following the conventional pipeline, the training dataset of a human activity recognition system relies on the detection of the significant signal variation regions. Such position-specific classifiers provide less flexibility for users to alter the sensor positions. In this paper, we proposed to employ the simulated sensor to generate the corresponding signal from human motion animation as the dataset. Visualizing the corresponding items from the real world, the user can determine the sensor's placement arbitrarily and obtain accuracy feedback as well as the classifier interface to get relief from the cost of a conventional training model. With the cases validation, the classifier trained by simulated sensor data can effectively recognize the real-world activity.

本文言語English
ホスト出版物のタイトルExtended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems, CHI EA 2021
出版社Association for Computing Machinery
ISBN(電子版)9781450380959
DOI
出版ステータスPublished - 2021 5 8
イベント2021 CHI Conference on Human Factors in Computing Systems: Making Waves, Combining Strengths, CHI EA 2021 - Virtual, Online, Japan
継続期間: 2021 5 82021 5 13

出版物シリーズ

名前Conference on Human Factors in Computing Systems - Proceedings

Conference

Conference2021 CHI Conference on Human Factors in Computing Systems: Making Waves, Combining Strengths, CHI EA 2021
国/地域Japan
CityVirtual, Online
Period21/5/821/5/13

ASJC Scopus subject areas

  • 人間とコンピュータの相互作用
  • コンピュータ グラフィックスおよびコンピュータ支援設計
  • ソフトウェア

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