Motion Estimation of Plush Toys Through Detachable Acceleration Sensor Module and Machine Learning

Kaho Kato, Naoto Ienaga, Yuta Sugiura

研究成果: Conference contribution

抄録

We propose a system that estimates motion in a plush toy by means of an attached sensor device and gives the user a sound feedback corresponding to the predicted motion. We have created several different types of detachable acceleration sensor modules as an accessory for the toy. This module can be attached at any position on a commercially available plush toy. The user can create original motions by teaching through demonstration, and the captured sensor data is converted into 2D image data. We extracted the histograms of oriented gradients (HOG) features and performed learning with a support vector machine (SVM). In an evaluation, we decided the attaching parts and motions in advance, and participants moved a plush toy in accordance with these. Results showed that it was possible to estimate the plush toy’s motion with high accuracy, and the system was able to register a sound for each motion.

本文言語English
ホスト出版物のタイトルHCI International 2019 - Posters - 21st International Conference, HCII 2019, Proceedings
編集者Constantine Stephanidis
出版社Springer Verlag
ページ279-286
ページ数8
ISBN(印刷版)9783030235277
DOI
出版ステータスPublished - 2019
イベント21st International Conference on Human-Computer Interaction, HCI International 2019 - Orlando, United States
継続期間: 2019 7 262019 7 31

出版物シリーズ

名前Communications in Computer and Information Science
1033
ISSN(印刷版)1865-0929
ISSN(電子版)1865-0937

Conference

Conference21st International Conference on Human-Computer Interaction, HCI International 2019
CountryUnited States
CityOrlando
Period19/7/2619/7/31

ASJC Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)

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