Future Challenges
Non-Frontal Face Recognitio

Results from an Open Book Challenge Problem, NOT an Inde

Still Vide

Results from December 
Cross mode face recognition

Visible vs near-infrared
Challenges in still frontal fac

2009 

Dalian UT Dalian UT To
“The Good, the B

&

the Ugly”

Still Face Challen
Goal of GBU

• Encourage development of face 

algorithms that work on “hard” to face pairs.

• Not at the expense of performanc

hard” face pairs. 
Method

• Three performance levels

– Good– Bad– Ugly

• Images in MBGC• Images included in FRVT 2006• Selected by FRVT 2006 algorithm
Experiment Specifics

• Nikon D70-6 Mpixels• Uncontrolled images

– Indoors– Outdoors

• 9,307 pool of images• 522 qualified subjects
Experiment Specifics

• Same number of images per subject

*

• Variation in performance on image attr

Data Set Target Size Query 

The Good 1046 104

The Bad 1046 104

The Ugly 1044* 104
Images per Subject
The Data Similarity Matrix

Target

Query

Match Score

Person 1

Match Score

Person 2-521

. . .
The Data cont.

• Good: High scoring match pairs• Bad: Average scoring match pai• Ugly: Low scoring match pairs.

Match Score

Person 1

Match Score

Person 2-521

. . .
Good Face Pairs
Bad Face Pairs
Very Challenging Face Pairs
Good, Bad, Ugly Performanc

?
Good, Bad, Ugly Performanc
Good, Bad, & Ugly ROC
Good, Bad, Ugly Technique

• Method for defining data sets of v

difficulty

• Applies to other biometric data se• Extend to ICE 2006 data set (ND
Region-based recognition

• Phillips, 1994, 1998• Moghaddam & Pentland, 1994• Jarudi & Sinha, 2003• Kumar, Berg, Belhumeur, & Naya
Summary-Face region

• Most important regions of the fac• Fusion across regions• Robust to occlusion and pose• Add region decomposition to GB
Summary

• Plenty of challenges in face reco

– Non-frontal– Illumination– Cross mode– Face Regions

• All are relevant to real-world app• Good, Bad, & Ugly iris
Summary

• Data available to support challen• MBGCv2

– Non-frontal still– Non-frontal video– Cross-mode

• Good, Bad, & Ugly

– Ready for release

• Face Region

– Based on existing challenge proble
Multiple Biometric Evaluation 

Update
MBE 2010 Tracks• .• The Still Face Track

– Reorganized

• Portal Track

– Based on portal challenge problem

• Video Track

– Based on video challenge problem
Still Face Track

• Large scale identification

– 1 million+ face people– Potentially 3 million people– Motivated by NGI– Applicable to large scale identificati– Lead: Patrick Grother

• Verification

– Improvement in still face recognition – Effects of compression and image r– Lead: Jonathon Phillips

• Organized as a single track
Questions addressed

• Effect of database size on perfor• Effect of multiple images of a per• Effect of meta-data

– Sex– Race– Date of Birth– Etc

• Application perspective• Scientific analysis
Still face track—schedule 

• 16 Nov 09: Initial draft evaluation plan release

• 30 Nov 09: Comments due 

• 9 Dec 09: Second draft evaluation plan releas

• 16 Dec 09: Comments due

• 18 Dec 09: Final evaluation plan released 

• 26 Jan 09—14 May 10: Submission period

• Sept/Oct 20: Report(s) released
Portal and Video tracks

• Data is based on MBGC 

– Portal: 3,000+ portal sequences– Video: sequences similar to MBGC

• Executable protocol

– Based on FRVT 2006 and ICE 2006

• Schedule

– 15 Dec 09: Evaluation plan release– March 10: Evaluation starts– Fall 10: Report(s) released
Information

http://face.nist.gov/m

mbe2010@nist.gov