Announcing Amazon Rekognition - Deep Learning-Based Image Analysis - December 2016 Monthly Webinar...
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Transcript of Announcing Amazon Rekognition - Deep Learning-Based Image Analysis - December 2016 Monthly Webinar...
© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
David Pearson
December 13, 2016
Amazon RekognitionEasy-to-Use Deep Learning-based Image
Recognition
Images – universal, ubiquitous, & essential
Images – explosive growth trends
Source: InfoTrends Worldwide Consumer Photos Captured and Stored.
2013 -2017 prepared for Mylio.
Amazon S3 – Images Stored
Images – explosive growth trends
Amazon Rekognition
Deep learning-based image recognition service
Search, verify, and organize millions of images
Object and Scene
DetectionFacial
Analysis
Face
Comparison
Facial
Recognition
DetectLabels
Object and Scene DetectionDetect objects, scenes, and concepts in images
Amazon Rekognition API
Amazon Rekognition API
DetectLabels
{
"Confidence": 94.62968444824219,
"Name": "adventure"
},
{
"Confidence": 94.62968444824219,
"Name": "boat"
},
{
"Confidence": 94.62968444824219,
"Name": "rafting"
},
. . .
Flower
ChairCoffee Table
Living Room
Indoors
Object and Scene Detection
Maple
Villa
Plant
Garden
Water
Swimming Pool
Tree
Potted Plant
Backyard
Object and Scene Detection
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.
Object and Scene Detection – Use CaseDynamic Search Indexing
AMAZON ELASTICSEARCH
AMAZON S3
Amazon Rekognition API
Facial AnalysisDetect face and key facial characteristics
DetectFaces
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”}
Demographic Data
Facial Landmarks
Sentiment Expressed
Facial Analysis
General AttributesImage Quality
Demographic Data
Facial Landmarks
Sentiment Expressed
General Attributes
Facial Analysis
Image Quality
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
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
Facial Analysis - Use Case (Retail – In-store and Online)
Demographic and Sentiment Analysis
AMAZON REDSHIFTAMAZON QUICKSIGHT AMAZON S3
Look Your Best All Day
Time for A New Look?
Pers
on A
Pers
on B
Sees
Sees
Facial Analysis - Use Case (Targeted Marketing)
Demographic and Sentiment Analysis
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
CompareFaces
Amazon Rekognition APIFace Comparison
Face-based user verification
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}
}
Face Comparison
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
Face Comparison – Use CaseFace-based Verification
AMAZON S3
Amazon Rekognition APIFacial Recognition
Index and Search faces in a collection
Index
Search
Collection
IndexFaces
SearchFacesByImage
Amazon Rekognition API
f7a3a278-2a59-5102-a549-a12ab1a8cae8
&
v1
02e56305-1579-5b39-ba57-9afb0fd8782d
&
v2
Face ID & face metadataFace
4c55926e-69b3-5c80-8c9b-78ea01d30690
&
v3tr
an
sfo
rme
d
sto
red
{
f7a3a278-2a59-5102-a549-a12ab1a8cae8,
02e56305-1579-5b39-ba57-9afb0fd8782d,
4c55926e-69b3-5c80-8c9b-78ea01d30690
}
IndexFace Collection
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
Facial Recognition
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
Facial Recognition - Use CasesIndexing faces into a collection
AMAZON S3
APPLICATION
Image Indexer
AMAZON
REKOGNITION
IndexFaces
Person Details
Application TableFace Collection
AWS LAMBDACAMERA
Live Frames
Facial Recognition - Use CasesSearch for similar faces in a face collection
AMAZON S3
Amazon Rekognition
Under the Hood
Amazon Rekognition – Feed Forward Inference
Layer 1 Layer 2 Layer n
…
Labrador
Dog
Beach
Outdoors
Cla
ssifie
r
Probability
Fully
Connected
Layer
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
Amazon Rekognition - Training Process
Training
SimpleAutomated Quality Fast
Data Pipeline
Amazon Rekognition - Training Process
GlobalTrained
&
Trusted
AvailableElastic
Human Workforce
Amazon Rekognition - Training Process
DEMO
Benefits
Fully Managed AWS Integration Low CostProven Scalability Secure
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
Amazon Rekognition – Pricing Details
Image Analysis TiersPrice 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.
Summary
1. Fully managed and easy-to-use image recognition service
2. Four primary capabilities1. 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
Getting Started
http://aws.amazon.com/rekognition/
Questions
Thank you
David Pearson