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This slide is an introduction of Rakuten Institute of Technology (R.I.T) and the “Reality Domain” team which specializes in Image Processing, Computer Vision, Ubiquitous Computing, HCI and UI/UX. It introduces some of our research topics and application to Rakuten’s services.
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Rakuten Institute of Technology
Jul/14/2014
Rakuten Institute of Technology
http://rit.rakuten.co.jp/
Value Proposition
Third Reality
Vision Locations
Rakuten’s Strategic R&D Organization
RIT: Rakuten Institute of Technology
Tokyo, New York,
and Paris
Rakuten (now)
Positioning
Basic
research
Applied study
Seeds study
Planning
By seeds
Planning
By needs Development Release Service
Rakuten (before)
R.I.T.
Academic
RIT connects technology seeds with service development, and provide
an engine to let Rakuten grow in the long term.
3 months to 1 year 1 to 3 years 3 to 5 years
Tokyo (40), NY (10) & Paris
New York Tokyo Paris
Global R&D Teams
Scientists Developing novel theories for novel technologies
Rakuten Institute of Technology
There are three roles in R.I.T. to develop/introduce advanced
technologies to Rakuten Services.
Developing Department / Business Units
Technologists Developing novel and efficient technologies
Coordinators Identifying and integrating technological needs from business units
Organizational Roles for Innovation
Research Area Focus
Rakuten Institute of Technology
Reality Domain
Introduction
Jul/14/2014
Reality Domain Group
Rakuten Institute of Technology
http://rit.rakuten.co.jp/
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Provide exciting new discoveries to customers via innovative presentation or interaction.
Deliver/extract more “Reality” via/from multimedia data.
Merge offline and online experiences to bring more value and “Entertainment” to shopping.
Online & Offline
Image Processing & Computer Vision
Next Generation UI/UX
Reality Domain Research Area
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Current Research Topics
10
Image Processing and Computer Vision
Image/movie processing, multimedia, computer vision
11
Poor quality Plural objects Wrong photo Text added image No image
Selected as the
‘best image’ Images evaluated as unsatisfactory
Recommended as the ‘Best’ image
Text-free image sorting focusing on quality resolution
Text Image Detection
新発売!
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MS EXCEL MS PPT
Web interface gives gray image on demand
Other old methods
Convert photos from color to gray while maintaining perceptual color contrast
Human perception focused - reduce colors to gray
keeping high contrast
2014 ICPRAM participated
Color Photo to Gray
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Next-Generation User Interface/User Experience
UI / UX
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Visualize the popularity and their attributes using human icons
Also you can watch this movie on YouTube
HITOKE: A Study of Queue Visualization of Internet Purchase Information
http://www.youtube.com/watch?v=cxVcTcZMXPs
Sync purchase information and visualize them as
human icons. Colors tell buyers’ attribute, so we
can know which clustered person likes this item.
HITOKE
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Fashion coordination interface for mobile device
swipe
give a function to try many coordination easily
by flicking smart phone screen, also changing
size and background functions are provided.
Published@CHI2013
Also you can watch this movie on YouTube
KiTeMiROOM: A Fashion-Coordination System for Mobile Devices
http://www.youtube.com/watch?v=S1VisIV28VY
Quick browse
Change situation (background)
Flexible sizing
Tuck-in/out coordination
KiTeMiROOM
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Picture based search interface for Rakuten Ichiba
Provide a novel interface for Rakuten Ichiba
search result, only showing item images to
bring a new discovery - serendipity.
Also you can watch this movie on YouTube
PicSer - Picture Based Search for Rakuten Ichiba
http://www.youtube.com/watch?v=QwJQbmCjCDk
Rich Image Window Shopping
Color Filtering
Similar Item Search
Image Grouping
Compare Items
Keyword addition & reduction
UIUX
NLP ImageProcessing
NLP
ImageProcessing
UIUX
UIUX
Providing many functions based on several basic technology
*PicSer
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Search interface for hand gesture
Also you can watch this movie on YouTube
KooSHO: an environment for Japanese text input based on aerial hand gestures.
http://www.youtube.com/watch?v=xurR3sYT08w
Recognize the letter
which a user gestured by
kinect
Natural Language
Proecssing
NLP engine provides
candidate queries with
inputted letter
“Randoseru”
“Reinco-to”
“Rryukkusakku”
User can select candidate
search keyword by touch
After selecting keyword,
user can watch particular
item by touch, of course
can buy it.
“R”
KooSHO
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Online <-to-> Offline (O2O)
Ubiquitous Computing, Augmented Reality, Virtual Reality
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Visualize the popularity of each items by human icons utilizing AR Technology
Prototype – show the popularity by
human icons in smartphone. Each
colored icon means the attribute of
buyer, men or women, young or old, and
so on.
Advanced version – for food exhibition
In this advanced version, users can get
information on the screen by putting REAL
flyer in front of the camera. The number of
human icons are calculated from POS data. Also you can watch this movie on YouTube
“AR HITOKE: visualize the popularity of REAL shops”
http://www.youtube.com/watch?v=RF1Rh7DGW6c
Original version
AR HITOKE
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Show the items and shops information utilizing digital signage
Also you can watch this movie on YouTube
Enriching Event Information Display with Touch Interaction
https://www.youtube.com/watch?v=OzB2J9wp_AE
The NET The REAL
Detailed item information,
Online user reviews, and so on
Access the website via QR code
R-WallSHOP
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Business Contribution
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Brighten and liven up a color of a dish
Yummy filter
Trim image into square (for list page) keeping important area
trim
Make dish images
more attractive
Find important area
Yummy Filter and Image Trimmer for Rakuten Recipe
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Visitors enjoyed fashion coordination easily.
It’s first time to introduce our technology to
general users directly.
Shared the coordination on facebook
Fashion Coordinate System for Events (March 2013)
KiTeMiROOM, fashion coordination
system to empower people to check
many coordination easily, speedy.
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HITOKE, show the popularity of each items by human icons
After applying, majority
product got more 2
times click/day and the
other reduce it by 30%.
HITOKE provided ‘bias’
It must be
popular!
HITOKE meets Rakuten24 (April-May 2013)
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Show demonstration at Nagoya Station, Umeda-Hanshin, Namba Takashimaya
The number of human icons
means each shop’s popularity.
This number is depended on the
real POS data.
Icon sometimes
speaks online
review.
AR HITOKE at department store events (Sep-Oct ‘13)
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Shop map in the
department store
Extracted text from user
reviews (picked by NLP
technology)
Lead to the
website
Show demonstration at Hakata Hankyu department store
Touch interesting item and detailed
information appears
R-WallSHOP at department store events
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Cross over the border of NET & REAL