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MRMW Singapore March 2014
Coding everything mobile: Introducing
Recognology
Mardien Drew
Head of Digital Incubation Team
2
Follow the consumer path…
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Caution: Image avalanche
Introducing Recognology
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Coding thousands of images
Sources of Images
• Mobile Diary Studies
• Extractions from Social
Media Sites
• Still extracted from Video
• Images from Life-blog or
Wearable Cameras
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Case study: Mobile beverage
consumption diary survey
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Combining automated coding with crowd
sourcing to improve accuracy
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Automated coding is not always the
solution – sometimes the crowd is best!
Coding/Tagging Techniques
• Use automated coding to
eliminate duplicates and
dark/blurry images
• Automated coding platform
groups similar user images
• Grouped images loaded to
Crowd Sourcing
• Final in-house QA.
Case study: WPP The Store’s Holiday Wrap
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Recognology - Object Recognition
challenges
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Recognology – Location/context
recognition
Coding/Tagging Techniques
• Use automated coding to
group images both by time
and by similarity
• We then end up with
manageable scenes which
we can then further explore.
• They were in a phone
• They were in a Café
• They were on a train
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Location mapping
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Brands travel through social media…
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And brands travel unintended…
What’s next?
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OCR= Optical Character Recognition
To summarise
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We need to do this now!– Volumes of images are huge and will only
increase with new devices with camera feature launched frequently.
Enhancing existing mobile offers - e.g. mobile consumption diaries
and path to purchase.
Learning – There are some challenges to overcome. Tech is not
optimal yet. But we have find an interim solution consisting of a
combined approach.
And we still need people!
Title Sponsor Gold Sponsor Silver Sponsors
Bag Sponsor Workshop Host
Sponsor
Event App
Partner
Networking Reception
Partner
March 4-7, 2014 Ramada Hotel, Singapore
www.mrmw.net
Association and Media Partners
March 4-7, 2014 Ramada Hotel, Singapore
www.mrmw.net
March 4-7, 2014 Ramada Hotel, Singapore
www.mrmw.net
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