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
January 2017
DOI

Abstract

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.

Type
Conference paper
Publication
Proceedings - International Conference on Multimedia Modeling (MMM)
3d human reconstruction Human reenactment Rgb-d sensors Sensing
Yuta Nakashima
Yuta Nakashima
Associate Professor

Yuta Nakashima is an associate professor with Institute for Datability Science, Osaka University. His research interests include computer vision, pattern recognition, natural langauge processing, and their applications.

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