National Science & Technolog

Interagency Working Group o

Dr. P. Jonathon PhillipsNational Institute of Standards an

National Science and T

Progress in Face Recognition ReseBiometric Infrast
National Science and Te

Start

Aug 2005 –

Dec 2006

Oc

D

May 2004 –

Mar 2006

BEE

Jan 2002 –

Present

Future

Directions
FRGC, FRVT 2005 & ICE Spon

Executing Agency

Sponsoring Agencies

Director of National Intelligence Intelligence Technology Innovation Center

– Science & Technology D– Transportation Security A
Background

Technology 

Development

Baseline 

July 2002 

May 2004 

–

Mar 2006
FRGC Goal and Objectiv

• The primary goal of the FRGC is to

Promote and advance face rec

technology to support U.S. Gove

recognition efforts
FRGC Goal and Objectiv

• The primary goal of the FRGC is to

Promote and advance face rec

technology to support U.S. Gove

recognition efforts

• The primary objective of the FRGC 

Develop still and 3D algorithms to 

performance an order of magnitud

2002
Grand Challenge Architec

Meta data• eye coordinates• pose• gender

Preprocessing/ReconstructionCompression

Image QualityMeasures

ComparisonAlgorithms/Systems

Modes

Accuracy of:

3D Sensors

3D from stills
FRGC Modes Examined

Single Still Outdoor/

Uncontrolled

3D S

vie

Multiple Stills
FRGC Experiments

• Exp 1: Controlled indoor still versus indoo• Exp 2: Indoor multi-still versus indoor mu• Exp 3: 3D versus 3D

– 3t, texture channel only– 3s, shape channel only

• Exp 4: Controlled indoor still versus unco

still
Summary of FRGC Resu

January 2005

Exp 1 Exp 2 Exp 3 Exp 3t Exp 3s Exp 4 

0.0 0.2 0.4 0.6 0.8 1.0

Experiment

Verification rate @ FAR = 0.001

University

Experiment

17 11 10

4

5 12
FRGC Progress

Exp 1 Exp 2 Exp 3 Exp 3t Exp 3s Exp 4 

0.0 0.2 0.4 0.6 0.8 1.0

Experiment

Verification rate @ FAR = 0.001

Jan 2005

Experiment

17 11 10

4

5 12

University
FAR = 0.1%

Independent Evaluations 

(Gold Standard)

Performance Goals and Prog

Starting Point 80%

Measured in

FRVT 2002
Starting Point 80%

Measured in

FRVT 2002

FAR = 0.1%

Independent Evaluations 

(Gold Standard)

Performance Goals and Prog

Goal 98%

To be measured 

by FRVT 2005
Starting Point 80%

Measured in

FRVT 2002

FAR = 0.1%

Independent Evaluations 

(Gold Standard)

Performance Goals and Prog

Goal 98%

To be measured 

by FRVT 2005

99.99% Multi-Still 

(Jan 05)

97% Three-Dimensi

(Jan 05)

Face Recognition 

(Qualified 

99% High Resolutio

(Jan 05)

* First set of results after 4 mo
Starting Point 80%

Measured in

FRVT 2002

FAR = 0.1%

Independent Evaluations 

(Gold Standard)

Performance Goals and Prog

Goal 98%

To be measured 

by FRVT 2005

99.99% Multi-Still 

(Jan 05)

97% Three-Dimensi

(Jan 05)

Face Recognition 

(Qualified 

99% High Resolutio

(Jan 05)

* First set of results after 4 mo
National Science and Te

Future Directions

• Face Recognition Advanced Study W

– 11-14 November 2005– West Virginia University, Morgan– Objective

• Intense technical discussions to identif

recognition

– Outcome

• Identification of technology gaps• Roadmap to bridge the gaps
Infrastructure Biometric Experi

Data (Lots)

50,000 images
Biometric Experi

Data (Lots)

50,000 images

Infrastructure
Data (Lots)

50,000 images

Infrastructure Biometric Experi
Biometric Experi

Data (Lots)

50,000 images

Infrastructure

•Multi-Modal Demonstr

• Conducted in the P
Data (Lots)

50,000 images

Infrastructure Biometric Experi

•Multi-Modal Demonstr

• Conducted in the P

•Applications to New Problem Domains

•NGA Adopts BEE Framework for STARS Pr
• Broad Goals

– Technology assessment of iris recognition

– Facilitate technology development

• Modeled after FRGC/FRVT 2005• Q: What portion of the iris recognition 

address?

– A: Recognition algorithms. ICE will provi
Questions Examined

Target Set 

Query Set Algorithm

Outpu

Similar

Matrix

Input

Recognition

Min | Seg AND Gnd |

| Seg XOR Gnd | , C

Input

Image

Segmentation

Algorithm

Ground Truth

Segmentation / Location Im
National Science and Te

Conclusion• Face Recognition Grand Challenge (FR• Face Recognition Vendor Test (FRVT) • Iris Challenge Evaluation (ICE)• Biometrics Experimentation Environme• Face Recognition Advanced Study Wor