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The Curved Surface Visualization of the Expert Behavior for Skill
Transfer Using Microsoft Kinect
Kaoru Mitsuhashi
1
, Hiroshi Hashimoto
2
and Yasuhiro Ohyama
1
1
School of Computer Science, Tokyo University of Technology, Hachioji, Tokyo, Japan
2
Master Program of Innovation for Design and Engineering, Advanced Institute of Industrial Technology, Tokyo, Japan
Keywords: Skill Transfer, Microsoft Kinect, B-spline Curve Surface, Visualization, Gradient Curvature Distribution,
Tracking Motion, Experts and Beginner.
Abstract: Method of teaching and inheriting for skill is almost oral. It is not quantitative but qualitative. Quantitative
inheriting of skill is difficult. In this paper, after tracking of a subject's skill motion using Microsoft Kinect,
a subject's motion is visualized as the curved surface. A curved surface is fitted in the positions of a subject's
joint, or the direction of trajectories. Expert and beginner perform swimming and karate motion. After the
motions are tracked, the trajectories of joints are transformed to a curved surface. The difference of an
action between an expert and a beginner is extracted by investigating curvatures and form on the visualized
curved surface. Therefore, we expected that technical skill is transferred easily.
1 INTRODUCTION
The actions at the time of dances, sports, and
engineering are different greatly to an expert and a
beginner. However, methods of teaching and
inheriting for skill is almost oral. It is not
quantitative but qualitative. Quantitative inheriting
of skill is difficult. In the case of sports, the experts
express in abstract languages, such as onomatopoeia,
or metaphor of an object image. However, they can’t
teach or inherit exactly and quantitatively. In the
case of engineering (Takeo and Natsu, 2011), the
experts can’t express a motion of fingertips and arms
orally in technical parts, such as machine tool
operation. Then, after seeing an expert's operation,
the beginner trains by performing imitated the
operation. In addition, the inheritance is impossible
when experts leave suddenly. Moreover, since
quantitative evaluation cannot be performed, the
same motion is not always repeated. Then, an
expert's motion is captured by video camera
photography, and the motions are analysed in
research or software (Cheung, Baker and Kanade,
2003), (Sigal and Black, 2006). The method is the
motion capture by one or more camera sets, with the
background subtraction technique, extracts a
human's outline and displays only a human's motion.
The motion can be preserved, and the reproducibility
is high. However the extraction of human position is
difficult, and quantitative evaluation is limited or no
meaning. Furthermore, in order that motion capture
may require large scale equipment, the possible
capture place is restricted in many cases. By forcing
marker wearing on a subject, we can hardly expect
to track the usual motion.
Then, we focus Microsoft Kinect, which is a
reasonable and easy operation, and capture the
motion using it. Kinect can recognize pictures and
depth positions, which is a useful tool function and
expected the application to three-dimensional
measurement. Kinect can extract a human's outline,
and the position of the human skeletons and joints.
Therefore, a human motion can be extracted easily
on a small scale. In the conventional research, angles
of the skeleton and joint positions are measured
(Murao, Hirao and Hashimoto, 2011). However,
there is no research that the whole body motion is
evaluated. Moreover, the quantitative evaluation of
joint angle and extracting position may be no
meaning. Namely, joint angle evaluation is not
transferred easily, and exact joint angles is not
necessary in many cases. In this paper, our purpose
is that a human joint position of motion is visualized
to a curved surface, and we extract the difference
between beginners and experts from the form or
curvature of the curved surface. We focus the human
upper half body, investigate the trajectories to the
both hands, elbows, shoulders, and the neck.
550
Mitsuhashi K., Hashimoto H. and Ohyama Y..
The Curved Surface Visualization of the Expert Behavior for Skill Transfer Using Microsoft Kinect.
DOI: 10.5220/0005101305500555
In Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO-2014), pages 550-555
ISBN: 978-989-758-040-6
Copyright
c
2014 SCITEPRESS (Science and Technology Publications, Lda.)