This was one of the posters at the OCWC Global 2011 meeting. Modified as ppt file to be uploaded here.

1. OCWC Global meeting 2011
Semi-automatic and easy creation of
learning friendly OCW video content
C
Satoshi SHIMADA1, TadashiNAKANISHI1, Akira KOJIMA1
and Y hi i FUKUHARA
d Yoshimi 2
1NTT Cyber Solutions Laboratories 2Meiji University
y j y

2. Motivation
Creating a learning-friendly edited video, for video sharing
g g y , g
on the web, is painful and time-consuming.
Take time
Good skills required
Costs money
How to make this process easy?
At the same time how to make edited video learning
time,
friendly ?
The goal is to automatically extract information from a
lecture video and use them to produce a better version of
the video.

3. Problem
We need to take a video and edit it.
The cost of video capture can be reduced by fix HD camera.
Wide angle HD camera can record whole of lecture.
However, HD video is not suitable for sharing on the Web.
, g
Because,
(1)File size of HD video is too large
(2)Slide in simple downsizing video
is
i unreadable
d bl
(3)The entire scene is boring
( ) Video captured by
fixed camera
Video editing manually takes much time
time.

4. Proposed method
Proposed method
Proposed workflow for the easy and better creation
Cature the entire scene to a video bird's-eye view
by Full HD camera
Video file is moved to Laptop
Automatic detection of important
Information Semi-automatic
S
Screen/Speaker/Slide change
/Sp a /S a g transformation
Post-production
Post production (Mixing)
Screen + Speaker +
Slide change information
produced video

5. Principle
1920 pixels
i l
- speaker
- Screen or black board
- atmosphere of hall
are assembled based on 1080 pixels
editing template
-projection di t ti of screen
j ti distortion f
-brightness of speaker
brightness Editing template A Editing template B
Editi t l t
are corrected
corrected.
720 pixels
400 pixels
i l

6. Video processing
Video processing
(1)Speaker detection find faces in the image
detection:
linear Interpolation is conducted for no face image
(2) SScreen d t ti
detection: fi d a rectangle under appropriate
find t l d i t
conditions, size and vertex angle
diti i d t l
Because th camera can b positioned almost everywhere
B the be iti d l t h
in the lecture room a homography is used to map the
room,
screen coordinates to a flat rectangle as if it was seen
from the front of it
it.
(3) Chaptering: Based on a subtraction method upon N
equidistant frames to determine if a ‘Slide change’ has
occurred or not in ‘Screen region’
S

7. Usability evaluation
15 Participants without prior knowledge were asked how
they reviewed the p
y post-processed video in comparison
p pa
with the original one.
g
Videos used: 4(=20min×2, 1hour×2) ,720×408 pixels
Comparison of M
C i f Mean O i i S
Opinion Score
Original video Proposed method
Original video
(simple down conversion) S
Screen visibility
y
Speaker visibility
Not boring
g
Presence
Overall impression
Post
P t processed video
d id for learning use 1 2 3 4 5
by the proposed method bad good

8. Other example
Other example
Original id
O i i l video
Facial search area Screen area set
by manually
Post processed video by the proposed method
at the b i of l
h begin f lecture at the middle of l
h iddl f lecture

9. Video sharing on the Web
Video sharing on the Web
Enhance the video sharing function by using
SceneKnowledge, which provides a user-friendly web
interface to view videos, annotate them and post comment.
Post-produced
P t d d
lecture video
Annotation
Chapter is displayed within a
certain
chapter of the
Comment input form video
SceneKnowledge: A Video scene-based video sharing and
comment posting system

10. How to use our software
How to use our software
SceneEditor is a client software implementing the proposed
method.
Minimum operation is as follows
1.
1 determine the editing duration
2. Set facial search area
3. Set clipping area of speaker
4. detect screen a a
. area
5. select or set an editing template
g p
6. comand video procressing
--- auto processing ---
Time required for automated post-production is;
post production
Roughly correspond to the time of the video itself

11. Empowering communities with ICT Innovation
SceneKnowledge: A Video-based Knowledge Sharing
System
Know-how
Know how extraction by scene-based video sharing
scene based
Overview
Utilizing video: SceneKnowledge Collective knowledge
A wide variety of knowledge and know-how is being lost due to changes in the structure stored by participants
of households coupled with Japan's low birth rate and ageing population. Although
Japan s Video
Vid contentt t
writing comments and
efforts are being made to preserve this heritage in video records, people do not obtain Q&A responses
makes movements
knowledge just by watching videos. Our proposed system splits video content into and situations easy Comments are linked
manageable units so that the corresponding knowledge and know-how can be
know how to understand to videos allowing
videos,
discovered and shared more easily. This system can be accessed remotely on PCs and users to quickly access
mobile terminals, allowing information to be shared widely in everyday situations and other scenes of
interest to them
providing a useful tool for lifelong learning and for invigorating communities
communities. Points reinforced
by visual
Features annotation New findings are
encouraged by
■ By watching in scene units it is possible to collect useful on topic comments.
units, on-topic comments comparing with
i ith
■ Users can search the comments to quickly discover other scenes of interest to them. appended videos
■ New discoveries can be made by comparing comments, attached videos etc..
■ Can also be accessed on mobile phones and touch-screen smartphones. Can be accessed
Lecture video slides anywhere by mobile
■ The optional Scene Editor tool incorporates lecture video material from universities phones or
and lecturer extracted
and the like to produce polished results
results. smartphones
and neatly arranged
Application scenarios Can also be used
for scene listings
g
■ To support e learning aimed at improving sports skills or technical ability*¹
e-learning Video analysis: Vk video handling library or for digest
■ As a forum for the sharing and exchange of knowledge within communities*² ーー
playback
ーー
■ As a forum for review and lifelong learning tied in with the delivery of university
g g y y ーー
ーー
ーー
Long videos cover
L id ーー
lectures*³
a mixture of many
■ As an in-house sharing site for corporate training and technology transfer different topics Indexes are added by video
■ As a system for archiving important video content and summarized video clips analysis to make the content
easier to grasp
*1 Tests conducted jointly with NTT Knowledge Square “N-Academy”
*2 Tests conducted jointly with Sakuho Town “Farming community support technology”
*3 Joint study with Keio University “JOCW”
3 JOCW
Contact: cc-forum@lab.ntt.co.jp Copyright © 2011 NTT. All Rights Reserved.