This session will introduce you to Amazon Rekognition, a new service that makes it easy to add image analysis to your applications. With Rekognition, you can detect objects, scenes, and faces in images. You can also search and compare faces. Rekognition’s API lets you easily build powerful visual search and discovery into your applications. With Amazon Rekognition, you only pay for the images you analyze and the face metadata you store. There are no minimum fees and there are no upfront commitments. To get started with Rekognition, simply log in to the Rekognition console to try the service with sample photos or your own photos. Join this session and learn more about Amazon Rekognition!

1. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Ranju Das
November 30, 2016
NEW LAUNCH! Introducing
Amazon Rekognition
Easy-to-Use Deep Learning-based Image Recognition
MAC203

2. Images – universal, ubiquitous, & essential

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

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

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

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

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

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

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
[
{
"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”}
DetectFaces

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

15. Demographic Data
Facial Landmarks
Sentiment Expressed
Image Quality
Facial Analysis
Brightness: 25.84
Sharpness: 160
General Attributes

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 S3AMAZON REDSHIFTAMAZON QUICKSIGHT

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

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
retrieve ad image
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
Face 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 & vector<float>Face
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
Nearest neighbor
search
Face ID

29. Face Recognition

30. Using Face 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. Face 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. Face Recognition - Use Cases
Search for similar face in Face Collection
AMAZON S3

33. Amazon Rekognition
Under the Hood

34. Ground Truth Generation
Training

35. Ground Truth Generation
SimpleAutomated Quality Fast
Data Pipeline

36. Ground Truth Generation
GlobalTrained ReliableElastic
Human Workforce

37. Amazon Rekognition - Deep Learning Process
Conv 1 Conv 2 Conv n
…
…
Feature Maps
Labrador
Dog
Beach
Outdoors
Softmax
Probability
Fully
Connected
Layer

38. DEMO

39. Benefits
Fully Managed AWS Integration Low CostProven Scalability Secure

40. 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

41. 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 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.

42. 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

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

44. Questions

45. Remember to complete
your evaluations!

46. Thank you!
Ranju Das