Amazon Rekognition is a service that makes it easy to add image analysis to your applications. In this webinar you’ll learn how to detect objects, scenes, and faces in images. This webinar will also introduce Rekognition’s ability to search and compare faces. You’ll also be introduced to Rekognition’s API, which enables you to quickly add sophisticated deep learning-based visual search and image classification to your applications. Learning Objectives: • Learn about the capabilities and features of Amazon Rekognition • Learn about the benefits of Amazon Rekognition • Learn about the different use cases • Learn how to get started using Amazon Rekognition • Understand what is included in the AWS Free Tier and how to estimate usage costs

1. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
David Pearson
December 13, 2016
Amazon Rekognition
Easy-to-Use Deep Learning-based Image
Recognition

2. Images – universal, ubiquitous, & essential

3. Images – explosive growth trends
Source: InfoTrends Worldwide Consumer Photos Captured and Stored.
2013 -2017 prepared for Mylio.

4. Amazon S3 – Images Stored
Images – explosive growth trends

5. Amazon Rekognition
Deep learning-based image recognition service
Search, verify, and organize millions of images
Object and Scene
Detection
Facial
Analysis
Face
Comparison
Facial
Recognition

6. DetectLabels
Object and Scene Detection
Detect objects, scenes, and concepts in images
Amazon Rekognition API

7. Amazon Rekognition API
DetectLabels
{
"Confidence": 94.62968444824219,
"Name": "adventure"
},
{
"Confidence": 94.62968444824219,
"Name": "boat"
},
{
"Confidence": 94.62968444824219,
"Name": "rafting"
},
. . .

8. Flower
ChairCoffee Table
Living Room
Indoors
Object and Scene Detection

9. Maple
Villa
Plant
Garden
Water
Swimming Pool
Tree
Potted Plant
Backyard
Object and Scene Detection

10. Using Rekognition Object and Scene Detection
 Photo-sharing apps can power smart searches
and quickly find cherished memories, such as
weddings, hiking, or sunsets.
 Vacation rental markets can automatically label
host-uploaded images with tags, such as
fireplace, kitchen, or swimming pool.
 Travel sites and forums can classify user
generated images with labels such as beach,
camping, or mountains.

11. Object and Scene Detection – Use Case
Dynamic Search Indexing
AMAZON ELASTICSEARCH
AMAZON S3

12. Amazon Rekognition API
Facial Analysis
Detect face and key facial characteristics
DetectFaces

13. Amazon Rekognition API
DetectFaces
[
{
"BoundingBox": {
"Height": 0.3449999988079071,
"Left": 0.09666666388511658,
"Top": 0.27166667580604553,
"Width": 0.23000000417232513
},
"Confidence": 100,
"Emotions": [
{"Confidence": 99.1335220336914,
"Type": "HAPPY" },
{"Confidence": 3.3275485038757324,
"Type": "CALM"},
{"Confidence": 0.31517744064331055,
"Type": "SAD"}
],
"Eyeglasses": {"Confidence": 99.8050537109375,
"Value": false},
"EyesOpen": {Confidence": 99.99979400634766,
"Value": true},
"Gender": {"Confidence": 100,
"Value": "Female”}

14. Demographic Data
Facial Landmarks
Sentiment Expressed
Facial Analysis
General Attributes
Image Quality

15. Demographic Data
Facial Landmarks
Sentiment Expressed
General Attributes
Facial Analysis
Image Quality

16. Using Rekognition Facial Analysis
 Photo printing service can recommend the best
photos to their users
 Online dating applications can improve their
match recommendations using face attributes
 Retail businesses can understand the
demographics and sentiment of in-store
customers
 Ad-tech services can display dynamic and
personalized content to customers

17. Facial Analysis - Use Case
(Retail – In-store and Online)
Demographic and Sentiment Analysis
Female
Happy
Smiling
Male
No Facial Hair
Happy
Female
Sad
No Eyeglasses

18. Facial Analysis - Use Case
(Retail – In-store and Online)
Demographic and Sentiment Analysis
AMAZON REDSHIFTAMAZON QUICKSIGHT AMAZON S3

19. Look Your Best All Day
Time for A New Look?
PersonAPersonB
Sees
Sees
Facial Analysis - Use Case
(Targeted Marketing)
Demographic and Sentiment Analysis

20. Facial Analysis - Use Case
(Targeted Marketing)
Demographic and Sentiment Analysis
demographic and
sentiment attributes
Look Your Best All Day
Application
AMAZON
REDSHIFT
AMAZON
DYNAMODBAMAZON S3
log
demographic
profile updates
face image is collected
and analyzed AMAZON
REKOGNITION
DetectFaces

21. CompareFaces
Amazon Rekognition API
Face Comparison
Face-based user verification

22. Amazon Rekognition API
CompareFaces
{
"FaceMatches": [
{"Face": {"BoundingBox": {
"Height": 0.2683333456516266,
"Left": 0.5099999904632568,
"Top": 0.1783333271741867,
"Width": 0.17888888716697693},
"Confidence": 99.99845123291016},
"Similarity": 96
},
{"Face": {"BoundingBox": {
"Height": 0.2383333295583725,
"Left": 0.6233333349227905,
"Top": 0.3016666769981384,
"Width": 0.15888889133930206},
"Confidence": 99.71249389648438},
"Similarity": 0
}
],
"SourceImageFace": {"BoundingBox": {
"Height": 0.23983436822891235,
"Left": 0.28333333134651184,
"Top": 0.351423978805542,
"Width": 0.1599999964237213},
"Confidence": 99.99344635009766}
}

23. Face Comparison

24.  IoT and camera manufacturers can integrate face-
based verification directly into their products
 Application of face comparison in locating person of
interest for Public Safety
 Hotels & hospitality businesses can provide seamless
access for guests and VIPs
 Online exams or polls can verify presence of registered
person by comparing against image captured by
webcam.
Using Rekognition Face Comparison

25. Face Comparison – Use Case
Face-based Verification
AMAZON S3

26. Amazon Rekognition API
Facial Recognition
Index and Search faces in a collection
Index
Search
Collection
IndexFaces
SearchFacesByImage

27. Amazon Rekognition API
f7a3a278-2a59-5102-a549-a12ab1a8cae8
&
v1
02e56305-1579-5b39-ba57-9afb0fd8782d
&
v2
Face ID & face metadataFace
4c55926e-69b3-5c80-8c9b-78ea01d30690
&
v3transformed
stored
{
f7a3a278-2a59-5102-a549-a12ab1a8cae8,
02e56305-1579-5b39-ba57-9afb0fd8782d,
4c55926e-69b3-5c80-8c9b-78ea01d30690
}
IndexFace Collection

28. Amazon Rekognition API
Face
{
f7a3a278-2a59-5102-a549-a12ab1a8cae8,
02e56305-1579-5b39-ba57-9afb0fd8782d,
4c55926e-69b3-5c80-8c9b-78ea01d30690
}
SearchFacebyImage Collection
High dimensional
space search
Face ID

29. Facial Recognition

30. Using Facial Recognition
 Family photo sharing apps can use face recognition
to group all faces of the same person in a family
 Entertainment and news organizations can index
decades of archived images to find celebrities
 Secure campuses / workplaces can use face search
to ensure all personnel in their facilities are
authorized to be there
 Public safety teams can leverage face collections to
automate tracking of persons of interest

31. Facial Recognition - Use Cases
Indexing faces into a collection
AMAZON S3
APPLICATION
Image Indexer
AMAZON
REKOGNITION
IndexFaces
Person Details
Application Table
Face Collection
AWS LAMBDACAMERA
Live Frames

32. Facial Recognition - Use Cases
Search for similar faces in a face collection
AMAZON S3

33. Amazon Rekognition
Under the Hood

34. Amazon Rekognition – Feed Forward Inference
Layer 1 Layer 2 Layer n
…
Labrador
Dog
Beach
Outdoors
Classifier
Probability
Fully
Connected
Layer

35. Amazon Rekognition - Training Process
1. Data sourcing
2. Data Annotation
3. Annotation Validation
… and do this in an iterative process
based on feedback from customer,
system and QA validation

36. Amazon Rekognition - Training Process
Training

37. SimpleAutomated Quality Fast
Data Pipeline
Amazon Rekognition - Training Process

38. GlobalTrained
&
Trusted
AvailableElastic
Human Workforce
Amazon Rekognition - Training Process

39. DEMO

40. Benefits
Fully Managed AWS Integration Low CostProven Scalability Secure

41. Amazon Rekognition – Availability and Pricing
1. Released General Availability
2. At launch available in 3 regions,
1. US East (N. Virginia)
2. US West (Oregon)
3. EU (Ireland)
3. Pricing
• Pay as you go
• Free Tier – 5000 images per month for first 12 months
• Tiered Pricing designed

42. Amazon Rekognition – Pricing Details
Image Analysis Tiers
Price per 1000
images processed
First 1 million images processed* per month $1.00
Next 9 million images processed* per month $0.80
Next 90 million images processed* per month $0.60
Over 100 million images processed* per month $0.40
*Images processed: For APIs with image as input, it’s the number of images analyzed. For APIs with no image input 1 API call = 1 image processed.

43. Summary
1. Fully managed and easy-to-use image recognition service
2. Four primary capabilities
1. Object and Scene Detection
2. Facial Analysis
3. Face Comparison
4. Face Recognition
3. Integrated with AWS and AI Services
• Amazon S3
• Lex and Polly
4. Scalable and low cost

44. Getting Started
http://aws.amazon.com/rekognition/

45. Questions

46. Thank you
David Pearson