Title: Usability Considerations for Face Image Capture at U.S. Ports of Entry NIST International Workshop o
1Usability Considerations for Face Image Capture
at U.S. Ports of EntryNIST International
Workshop on Usability and Biometrics June 23-24,
2008 Lawrence D. Nadel, Ph.DNoblis
2Agenda
- US-VISIT background
- Potential face recognition applications in
US-VISIT - Port of entry (POE) operational environments
- Usability considerations
3US-VISIT Background
- US-VISIT provides biometric identification and
analysis services to agencies throughout the
immigration and border management, law
enforcement and intelligence communities - US-VISITs services help decision makers
accurately identify people and assess whether
they pose a risk to the United States - Biometrics captured from non-US citizens, ages
14-79 - Biometrics captured at Entry enhances security
and facilitates legitimate travel - Fingerprints
- 10P enrollment/background check, four-finger
verification - Exit verification (under development)
- Facial image
- Human verifiable traveler history
- Currently no automated face recognition
- Biometrics captured at Exit (to be determined)
identify overstays, crosscheck watch lists
4Applications for Face Imaging/Recognition
- Human comparison
- Compare live photo with visa and/or past photos
for visitors who have not been fingerprinted - Compare live photo with e-Passport photo for
first time Visa Waiver Program visitors - Increase verification confidence through decision
level or score level fusion - Supplement fingerprint check for detecting
aliased (duplicate) records or fraud - Search face-only watch lists
5Diversity of Operational Environments,Use Cases,
and Travelers
- POE types
- Land pedestrian, car, truck, bus
- Air small plane, jumbo jet
- Sea small boat, cruise ship
- Ambient environment - indoor/outdoor
- Variable illumination - day/night, directional,
multi-spectral - Entry formal inspection stations
- Exit little or no inspection infrastructure
- Travelers
- Cooperative, non-cooperative, uncooperative
- Multiple languages, cultures, appearances/clothing
- Hands full - luggage, packages, small children
6Air POE Environment
- Key factors for face recognition
- Pose angle
- Interocular pixel resolution
- Illumination
- Subject distance from camera
- (head size, distortion)
- Background
7Land POE Examples
Pedestrian Exit
Entry
8Usability-Related Interactions
Workstation/ System
Traveler
CBP Officer
9Cooperative Traveler
- Indicate that a picture is being takenwhere and
when - Image capture sensor should look and sound like a
camera - Provide simple and clear guidance (oral/written,
foreign language, still images, video) - Limit physical degrees of freedom, e.g., indicate
where feet should be placed on floor to control
distance to camera - Accommodate traveler whose hands may be occupied,
e.g., baggage, small child - Align camera with users faceaccommodate
variable height (short/tall, standing,
wheelchair) multiple cameras, portrait mode,
wide field of view digital camera
10Non-cooperative Traveler
- Human factors engineering to direct travelers
gaze at camera and have traveler pause for photo
no conscious effort on part of traveler
required - Printed signage
- Video display (static or variable)
- Strategic chokepoint
- Top of escalator
- Turnstile
- Portal
For US-VISIT Exit
11CBP Officer
- Officer needs to review documents, operate
workstation, and interview and observe traveler.
Position equipment to minimize officer movement
and minimize use of peripheral vision. - Simple and logical workstation GUI.
- For officer positioning of camera, show geometric
overlay on video screen to indicate proper
placement and size of image to be captured.
Provide easy to use automated or manual camera
control.
12Workstation/System
- Audio-visual feedback to both traveler and
officer - Automated image capture (quality in the loop)
- Automated control of camera focus, exposure
- Electronic control of pan-tilt-zoom (PTZ) camera
- Automated face finding and quality assessment
algorithms - Select image
- Crop
13Quality-in-the-Loop Face Image Quality
Improvement and Face Recognition Study
- Select and assess representative cameras
- Webcams
- Video with Pan-Tilt-Zoom
- Digital Still
- Wide Dynamic Range
- Select and assess several face quality metric
software tools - Inter-eye distance, head position, face contrast,
lighting uniformity,
- Integrate selected cameras capture photos and
video streams run image quality software
post-capture to assess impact
- Determine best hardware/software combination
integrate to run real time assess potential
impact on image selection
14Simulated Demonstration of Quality in the Loop
for Image Selection (Webcam)
(0-10)
(sec.)
15Discussion
- Lawrence D. Nadel, Ph.D.
- Phone (703) 610-1677
- Email nadel_at_noblis.org