TY - GEN
T1 - Remagicmirror
T2 - 23rd International Conference on MultiMedia Modeling, MMM 2017
AU - Dayrit, Fabian Lorenzo
AU - Kimura, Ryosuke
AU - Nakashima, Yuta
AU - Blanco, Ambrosio
AU - Kawasaki, Hiroshi
AU - Ikeuchi, Katsushi
AU - Sato, Tomokazu
AU - Yokoya, Naokazu
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
KW - 3D human reconstruction
KW - Human reenactment
KW - RGB-D sensors
UR - https://www.scopus.com/pages/publications/85009775871
UR - https://www.scopus.com/pages/publications/85009775871#tab=citedBy
U2 - 10.1007/978-3-319-51811-4_25
DO - 10.1007/978-3-319-51811-4_25
M3 - Conference contribution
AN - SCOPUS:85009775871
SN - 9783319518107
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 303
EP - 315
BT - MultiMedia Modeling - 23rd International Conference, MMM 2017, Proceedings
A2 - Amsaleg, Laurent
A2 - Gudmundsson, Gylfi Thór
A2 - Gurrin, Cathal
A2 - Jónsson, Björn Thór
A2 - Satoh, Shin’ichi
PB - Springer Verlag
Y2 - 4 January 2017 through 6 January 2017
ER -