L. Nadel – Intl Workshop on Usability and Biometrics June 23-24, 2008 1 Usability Considerations...

L. Nadel – Int’l Workshop on Usability and BiometricsJune 23-24, 2008

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Usability Considerations for Face Image Capture at U.S. Ports of Entry

NIST International Workshop on Usability and Biometrics June 23-24, 2008

Lawrence D. Nadel, Ph.DNoblis


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Agenda

US-VISIT background Potential face recognition applications in US-VISIT Port of entry (POE) operational environments Usability considerations


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US-VISIT Background US‑VISIT provides biometric identification and analysis services to

agencies throughout the immigration and border management, law enforcement and intelligence communities

US‑VISIT’s 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


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Applications 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


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Diversity 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


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Air POE Environment

Key factors for face recognition– Pose angle– Interocular pixel resolution– Illumination– Subject distance from camera

(head size, distortion)– Background


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Land POE Examples Pedestrian Exit

Entry


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Usability-Related Interactions

Workstation/

System

CBP Officer Traveler


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Indicate that a picture is being taken—where 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 user’s face—accommodate variable height

(short/tall, standing, wheelchair); multiple cameras, portrait mode, wide field of view digital camera

Cooperative Traveler


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Non-cooperative Traveler* Human factors engineering to direct traveler’s 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


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CBP 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.

(Illustration courtesy of

NIST Usability Group)


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Workstation/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


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Quality-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

Determine “best” hardware/software combination; integrate to run real time; assess potential impact on image selection

Integrate selected cameras; capture photos and video streams; run image quality software post-capture to assess impact

Select and assess several face quality metric software tools– Inter-eye distance, head position, face contrast, lighting uniformity, …


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Overall Quality vs. Time

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Time

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Simulated Demonstration of “Quality in the Loop” for Image Selection (Webcam)

(sec.)

(0-1

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Discussion

Lawrence D. Nadel, Ph.D.Phone: (703) 610-1677

Email: [email protected]

L. Nadel – Intl Workshop on Usability and Biometrics June 23-24, 2008 1 Usability Considerations...

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