Remagicmirror: Action learning using human reenactment with the mirror metaphor

Fabian Lorenzo Dayrit, Ryosuke Kimura, Yuta Nakashima, Ambrosio Blanco, Hiroshi Kawasaki, Katsushi Ikeuchi, Tomokazu Sato, Naokazu Yokoya

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

2 被引用数 (Scopus)

抄録

We propose ReMagicMirror, a system to help people learn actions (e.g., martial arts, dances). We first capture the motions of a teacher performing the action to learn, using two RGB-D cameras. Next, we fit a parametric human body model to the depth data and texture it using the color data, reconstructing the teacher’s motion and appearance. The learner is then shown the ReMagicMirror system, which acts as a mirror. We overlay the teacher’s reconstructed body on top of this mirror in an augmented reality fashion. The learner is able to intuitively manipulate the reconstruction’s viewpoint by simply rotating her body, allowing for easy comparisons between the learner and the teacher. We perform a user study to evaluate our system’s ease of use, effectiveness, quality, and appeal.

本文言語英語
ホスト出版物のタイトルMultiMedia Modeling - 23rd International Conference, MMM 2017, Proceedings
編集者Laurent Amsaleg, Gylfi Thór Gudmundsson, Cathal Gurrin, Björn Thór Jónsson, Shin’ichi Satoh
出版社Springer Verlag
ページ303-315
ページ数13
ISBN(印刷版)9783319518107
DOI
出版ステータス出版済み - 2017
外部発表はい
イベント23rd International Conference on MultiMedia Modeling, MMM 2017 - Reykjavik, アイスランド
継続期間: 1 4 20171 6 2017

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
10132 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

その他

その他23rd International Conference on MultiMedia Modeling, MMM 2017
国/地域アイスランド
CityReykjavik
Period1/4/171/6/17

All Science Journal Classification (ASJC) codes

  • コンピュータ サイエンス(全般)
  • 理論的コンピュータサイエンス

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