Toward Sports training service with the interactive learning platform1

1

2

Hiroyuki Okamoto , Alessandro Moro and Atsushi Yamashita and Hajime Asama

2

1RITECS Inc., 19-0032, Japan
Tel: +81 42 5234303, Fax: +81 42 5234303, E-mail: okamoto@ritecs.co.jp
2
The University of Tokyo, Tokyo
Abstract
In recent years, sports population has increased by health-oriented and improvement of sports environment . We
propose a platform that leaders and learners are able to share the training content with Interactive training and can befeedback to leaders. The platform is intended to create the learning result jointly by the leaders with the learners andleaders to update the learning content. The proposed solution helps to get the skills on a desired sport even in absenceof a real trainer by analysis of video data..

Keywords:
Computer vision , Form analysis , e-learning ,VR, Sport training
1 INTRODUCTION
In recent years, the World competition and Olympic
Games contributed to increase the population interested
in sports and that aim to practice one. The sports
population has increased by health-oriented andconvenient-to use sports environment . However, theincrease in popularity of different disciplines and theincrease of the Learners, make the access ofprofessional trainer difficult for time or area limits. For
learners who has limited resources, since the training
under a leader guidance requires a long time, and thelocation is often limited, the training instruments are fromthe WEB site (YouTube, etc.) and books. Such approachgives usually limited results and drives to mistakes andmisunderstanding. We propose a platform that leaders(provider) and learners (recipient) are able to share thetraining content with Interactive training and can be
feedback to leaders. The platform is intended to create
the learning result jointly by the leaders with the learners
and leaders
to update the learning content. The
technology of platform is based on the robotics
constituting from computer vision and data database andInternet and the control. The platform is possible tocomparison and analysis of the training content with a
combination of computer graphics and real image . Levelof understanding than the training of only normal text andmovie can be improved. Therefore, it is possible toprevent injury or failure due to incorrect operation. The
platform can be selected variously learning opportunities
and locations for running on WEB. At the moment,We
can measure the biometric during sport with smartphoneby the development of wearable sensors . Measurement
data is sequentially transmitted by Bluetooth to thesmartphone. Data will be saved in the smartphone, or isrecorded in the server on the network. The service
providers is very difficult to to detect the needs ofusers.Therefore, in some cases, the service supply isdelayed. Thus, a technique for constructing a network by
the service media[1] have been proposed. t is also
possible to understand that assess the needs of users
early with using this platform. In this paper we aim to
give a virtual guidance to the user taking advantage ofthe most advanced communication technologies. The
proposed solution helps to get the skills on a desired
sport even in absence of a real trainer by analysis ofvideo data.

Fig.1 Provide learning contents
2 CONSTITUTION
Platform is composed of a dedicated application andserver and advisor application .The dedicated application
running on the camera-equipped terminal .The serverstoring the learning content .The service advisorapplication is support the analysis and content building.
Sports learning is possible anywhere if meet theconditions. Leaders and learners carry out the creation ofimaging and analysis, and content by camera-equipped
terminal. A few years ago, it was necessary to shoot witha dedicated camera to obtain an image for sports
training. Current
the camera-equipped terminal ispossible to obtain an image necessary for sports training.
Recording time was longer by the capacity increase ofmemory. However, the memory capacity to perform
image recording to the server with streaming technology
because there is a limit. It is also possible to perform
sports learning by video call application. Learners can be
efficiently learning , because interact directly. Learning by
the video call application such as Skype have been
carried out in such as English conversation. However,sports learning by video call application is required time
adjustment. It is because there is a need to be connected
simultaneously. Sports learning is difficult to choose fromunspecified number of leaders like English learning.
Sports learning has many kinds Unlike English learning.
Another way there is a video learning. Learners will learn
to look at the "YouTube" and video was created byleaders. Learner hope to be able to sport learning
anytime, anywhere. This way , it is necessary to learners
to understand yourself the intent of the leaders. If thelearner is a mistake, progress is slow or physical failure
occurs . Because they can not be leaders and dialogue,
the learner need to interpolate the content that has been
omitted by the leader. This interpolation can be learners
progress is fast. Terminals and servers are connected via
a network at all times. Learning content is stored on theserver. Learning content is stored in a database fromsuch learning records and guidance content. Learning
content can be search by such date. Service advisor
application is an application running on the server.
Service advisor app presents the guidance content andleaders to learners from the contents of the sport to learn.

competition [2]. We became possible to see the timedifference between competitors in speed skating visually.
The following compares the form video in squat.

Fig.4 The compares the form video in squat.
3.2 The multi-motion
Method of multi-motion is a special image that isgenerated by the combined tension by extracting theactive part in the form image. It is possible tocontinuously analyze for visualization by afterimage effectform. Sporting event is finished the motion in a moment.
Continuity of the foam can not be visualized to be playedin slow the form image. Continuously visualized form
with multi-motion [3] in gymnastics. Kato et al. [4] haveused in golf and baseball form analysis.
Fig.2 Supplies the content

3.3 Analysis by skeleton model image
Image comparison and multi-motion is analyzed with avideo playback. However, since there is no feature pointin the video only, the learner it is difficult to grasp thelearning point. Recently, application of learning by using
the skeleton model image synthesizing human skeleton
model image by using an RGB-D sensor is alsopresented. We have synthesized a skeleton model thatgenerate from the form video .[5][6]Fig.3. Update the learning contents with Platform
3 FORM ANALYSIS
Learning by the video is believed to be effective in sports
learning. This is different from the process used in theimage inspection device of the production line.
It is also different from the process as a suspicious
individual detected by the monitoring camera. Here, we
do the visualization and data of the action from the videoby computer vision. We use the form image as the action
video. Typically, it is often used to the compare images ormulti-motion in order to visualize the operation image.
There are many applications for visualizing the operation
image by the development of the camera with theterminal. Method of Video comparing is play multiple
images at the same time in the display . Method ofcomparing the video can visually compare it to yourself
and others in order to display the operation at the sametime. Multi-motion generates an image by sequentially
updated only video part with using a motion vector.It iseffective in multi-motion form analysis.
3.1 The video comparison
Image comparison is a video to play at the same time byadjusting the playback start timing of the plurality ofimages. This approach is to show the your form and themodel form of leaders on the same screen. And updates
the learning content by comparing the form. In 1998
Nagano Olympics used in the video of the speed skating

Fig.5 skeleton model image-1

Fig.6 skeleton model image-2

Fig.7 stand of skeleton model

3.4 Learning content
Normally, the content of sports learning creates byleader for an unspecified number of learners. Learnerperforming learning to understand the description of theleaders. In this case, leaders satisfied with the learning
content, but learner is not satisfied unless growing
yourself. If the learner is not satisfied, leaders do notprovide service. We were able to build a content thatsuits his by the learner to update the content using theanalysis results with the form image. If the learner issatisfied advice leaders, the learner may incorporate thecontent of the leaders in the learning content. Also
improved leader of satisfaction by the feedback toleaders the built-in events in the learning content. The
event contains the evaluation factor. Currently, thisplatform cannot measure the level of satisfaction.
Evaluation of satisfaction in this platform is carried out by
the evaluation factor. Learning content is stored on thedatabase. Learning content is being constructed to linkthe video and data in the a text that serves as a base.
Database are managing learning content and learning
history. In the platform is able to display the history list
was learned by the search function. Sports learning is
performed repeatedly until a satisfactory result bychanging the learning method (content). This is afeedback loop. Learner is not only mind and feel, can beevaluated and analyzed by past history data. Even if I feelthat baseball is the pitcher is throwing in the same form,
there is a case the form is slightly different. In that case,in order to change the form by physical changes orconditions, past and present data comparison isimportant. Necessarily have to return to the previous form
is not the purpose, the learning content is updated daily.
Service advisor app advise with the accumulated data.

Fig8 skeleton model image in squat

Fig.10 Learning contents with Platform

Fig.9 create skeleton model

4 CONCLUSION
We learn by the video and leaders and learners has
been described platform to create a learning content
jointly in sports learning. Sports learning is necessary tocorrespond to the learner individual content and theory .
Theory of various sports is possible learning in books andvideo today. However, in order to learner is satisfied with
the individual has to be to update the learning content bylearners and leaders. Rather than build a system
individually a combination of existing products leadersand learners, is more efficient that was learned on thebasis of the platform. Learning content further scalability,
promote research to improve flexibility ． Currently, ourplatform, cannot be measured for satisfaction. We expectthat the sports to improve by the good service with thepresent platform for many children. In the future, we willproceed with the service advisor app of intelligence andform analysis on the WEB by attention to the research[7] of satisfaction measurement.
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