Goals

• Enable consumers & enterprises to move to a secure, password free world – inclusive of device unlock, payments, and secure content

• Develop hardware solutions that meet or exceed customer expectations for seamlessness, robustness, and ease of use

• Deliver biometric devices that embrace innovation and deliver customer value

• Create a more personal computing experience that makes technology interaction natural, rather than intrusive, so users can quickly get to work, or play

1. Head orientation

2. Find face & discover landmarks

3. Representation vector

4. Decision engine

:)

Find a FaceBuild Vector

based Representation

Does it match a Template?

Discover Landmarks

Detect head

Orientation

Step 4: Decision Engine

Step 3: Representation Vector

Step 2: Find Face & Discover Landmarks

Step 1: Head Orientation (Frontal Face)

Test environment/lab setup and testing process is outlined providing guidance on how to meet the current specification requirements

FilterFrame

PairingUniformity Gamma Ambient Saturation IRSNR MTF 50 MTF 50

MTF

Over/UndershootDistortion

30nm+- Yes/No< 65% @

Mid-range

Pixel to

Reflectivity

R² > 0.98

Incandescent light

For ALS (Ambient

Light Subtraction)

test

face in illuminated

frame can't be

saturated

@ near/far range

> 30/26/22 Full

FOV @ far range.25 < cy/pxl

.25 < cy/pxl

@ far range

< 5% / 3%

@ far range < 5.5%

Center Corner Center Center Corner Over Under

passYes

45% 0.99 0lux No ALS Pass 31 30 0.256 0.254 0.25 3.2% 1.0% 2%

50lux ALS Pass 27 26 0.223 0.23 0.21 4% 2%

150lux ALS Pass 23 22 0.2 0.21 0.2 5% 3%

300lux No ALS Pass

2

Test Environment

Image Signal Processing Tuning

ISP tuning artifacts interfere with face

authentication algorithms

0

10

20

30

40

50

60

70

80

90

100

400 500 600 700 800 900 1000 1100

Op

tica

l T

ran

sm

issio

n (

%)

Wavelength (nm)

aoi=0

aoi=30

Need to ensure that we have sufficient IR illumination at edge of sensor – impacts IR SNR, and overall device performance

Simple pixel-by-pixel ambient subtraction can yield image artifacts

Microsoft algorithm aligns marker positions to perform ambient subtraction

Key Advantages:

• Motion invariance

• Reduction in artifacts

Requirement:

• 15 FPS for Ambient and Illuminated frames

Artifact

Microsoft

Ambient

Subtraction

Pixel-by-

Pixel

Subtraction

Light-field

Artifacts

Artificial

Shading

Dark

Marking

Poor Edge

Delineation

• Same framework / interface used in other SKUs

• Built-in or Peripheral, Touch vs Swipe, Requirements

• Improve resiliency to threats (recommendations)

• Ensure the device / driver meets the security bar for publishing on Windows Update

• Driver built for x86 desktop can be recompiled to work on ARM

• From IHV perspective, process of creating driver is same for all SKUs

• Requires work with ODM to build BSPs

• Some IHVs already have experience in this area (ex. FPC, Synaptics) other’s don’t and so those IHVs will need to work closely with QC and the ODM to understand how to integrate their driver into a mobile BSP for Windows Phone

• Driver documentation and samples available on MSDN

• Variety of options make this an easy path to enabling Windows Hello

• Touch sensor recommended (better user experience)

• No difference in implementation or requirements

• False Accept Rate (FAR) < 0.001% (large sensor) < 0.002% (swipe and small sensor)

• False Reject Rate (FRR) < 5% without anti-spoofing

• False Reject Rate (FRR) < 10% with anti-spoofing

• Anti-spoofing solution is required

• Full details available on MSDN and Connect

• Size – 10mm x 10mm

• Bus – SPI or USB (SPI preferred)

• Power - <= 100mW during capture and <= 1mW otherwise

• Better performance

• Spoofing and replay attacks

• Injection of biometric samples

• Template theft and injection

• Attacks by privileged code on a compromised system

• Protect biometric input, from raw data collection through template matching

• When possible utilize “advanced sensors” capabilities to perform match on chip

• Isolate biometric operations and template management with TrustZone

• Implementation details available on Connect (V4 engine adapter interface)

• Partner to provide report on how FAR results were achieved

• Partner to submit results via SysDev bug for security review by feature team

• Provide sensor samples (~10) for self-host validation

• Full details of security review can be found on Connect

Please provide feedback on this session:

aka.ms/winhecfeedback