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FINAL PRESENTATION HiMax: Facial Biometrics With a CogniMem Device (Neural Processor)

FINAL PRESENTATION HiMax: Facial Biometrics With a CogniMem Device (Neural Processor). Presentation Overview:. Team and Member Introduction Brief Project Overview Block Diagrams - Controlled Environment (Standard and Variable Settings) - CogniMem Device and Software Development Kits

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FINAL PRESENTATION HiMax: Facial Biometrics With a CogniMem Device (Neural Processor)

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  1. FINAL PRESENTATIONHiMax: Facial BiometricsWith a CogniMem Device(Neural Processor)

  2. Presentation Overview: • Team and Member Introduction • Brief Project Overview • Block Diagrams - Controlled Environment (Standard and Variable Settings) - CogniMem Device and Software Development Kits - CogniMem Device (Details) - Laptop Temporary Setup & Training (CogniSight Control Panel) Approaches • Phase 1 (Completed); Discussion of results and “lesson-learned” • Phase 2 (ON-HOLD); Controlled Group Characterization • Phase 3 (ON-HOLD): Un-controlled Group (Noise) Introduction • Phase 4 (Maybe): It depends on Phase 2 & 3 results. • Got Problems!? (Yes, we hadsome!) • End of Semester Project Goals • Project Timeline • Presentation Summary • Q&A session

  3. FINAL PRESENTATIONHiMax: BiometricsWith a CogniMem Device(Neural Processor) Members: Raymundo Flores James Cuaresma EE Advisor: Dr. Tep Dobry ICS-Sub Advisors: Dr. Neil Scott Dr. Winyu Chinthammit

  4. Project Overview: This technology is fairly new, so we propose: • Research methodology for an “efficient training” of the CogniMem Neural processor. • Concurrently, develop “reproducible procedures” for a "high-level confidence" for “Facial Biometric recognition” application in a static physical environment. • As needed, create hardware interface with the device; develop software for a particular application.

  5. Block Diagram:Controlled Environment Diagram Top View Standard Settings: - Method of training: Easy-Video Recognition - Image Recognition Type: Moderate - Region Of Interest (ROI): (244,126)-(208,195) - Light elevations: 65.5”Variable Settings - Refer to Scripted Matrix Call-out Side View

  6. Block Diagram:CogniMem Device and Applications

  7. Block Diagram:CogniMem Device (Details)

  8. Block Diagram:Laptop Temporary Setup & Training (CogniSight Control Panel)

  9. Approaches: • Phase 1 (Completed) • Create a “controlled environment” to characterize the Biometric limits of the CogniMem device with respect to known environmental changes (more elaboration is just a sec). • “Lesson learned “ comprehensive review of result (completed). • Phase 2 • With lesson learned in Phase 1 and suggestions from advisors, will implement a controlled-group “open environment” characterization/testing of the device (more elaboration is just a sec). • Phase 3 • Introduce testing of the uncontrolled-group (False-Positives) • Phase 4 • Control group & Uncontrolled Group unscripted open-environment testing.

  10. Phase 1: Results • Result Discussion: • Lighting Variation Effects • External Facial Accessories Variation Effect • Facial Change Variation Effects • Facial Expression Variation Effects

  11. Phase 1: Lesson Learned • Perform training in “general office lighting environment” • “Zoom-in” ROI size to facial contour. • If possible, set camera configurations to “manual mode” (i.e. shutter speed, gain, etc.) • First neuron committed should be on the background environment. • CogniMem device is somewhat unstable. - Froze 3X (after 10, 2 & 40 minutes of operation). - Uncontrolled neuron assignment.

  12. Phase 1:Region Of Interest Phase 2:Region Of Interest

  13. What’s next?Phase 2 (On-Hold) • Phase 2 • With lesson learned in Phase 1: • Will implement a controlled-group “open environment” characterization/testing/modified deception testing of the device. • Concurrently, research causes for the • CogniMem to “freeze” • Uncontrolled neuron assignment • USB port assignment erratic

  14. What’s next?Phase 3 • Phase 3 • Introduction of uncontrolled group (noise) to characterize “False-Positive” recognition. • Control group (thru external & facial manipulation) to deceive & create “Positive  Unknown” identification

  15. What’s next?Phase 4 • Phase 4 • Control group (with external & facial deception) and uncontrolled group unscripted open environment testing. • Real life simulation.

  16. Problems (Yes, we have them): • Hardware & Software • CogniMem becomes unresponsive • Uncontrolled neuron assignments (without any keyboard or mouse activity); normally happens right after the CogniMem device becomes unresponsive. • USB port assignment erratic • Legal (Privacy) Issues • Privacy Act of 1974 • Letters and Forms • Consent Letter • Protection, handling, storage, and use of collected ‘digital facial biometric information’. • Inter-Disciplinary Dynamics (EE-ICS) • Professional conflict goal resolution.

  17. End of Semester Project Goals: Our projected goals are: • Develop efficient training methodology of the CogniMem device. • Develop “reproducible procedures” for a "high-level confidence" Biometric recognition training. • Have a working model for a static Facial Biometric identification that is reliable. • Hopefully, find solutions to the hardware and software problems we are experiencing to have a more stable system. • EE496: Lay the ground-work for a “dynamic” Facial/Body Biometric follow-on project.

  18. ?Any Questions?

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