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PRELIMINARY DESIGN REVIEW HiMax: Facial Biometrics With a CogniMem Device (Neural Processor). Presentation Overview:. Team and Member Introduction Brief Project Overview Approaches Phase 1 Phase 2 Phase 3 Possible Problems ( guarantee there will be some!) End of Semester Project Goals
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PRELIMINARY DESIGN REVIEWHiMax: Facial BiometricsWith a CogniMem Device(Neural Processor)
Presentation Overview: • Team and Member Introduction • Brief Project Overview • Approaches • Phase 1 • Phase 2 • Phase 3 • Possible Problems (guarantee there will be some!) • End of Semester Project Goals • Project Timeline • Presentation Summary • References • Q&A session
PRELIMINARY DESIGN REVIEWHiMax: BiometricsWith a CogniMem Device(Neural Processor) Members: Raymundo Flores James Cuaresma Advisor: Dr. Tep Dobry Sub Advisor: Dr. Neil Scott Dr. Winyu Chinthammit
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.
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
Block Diagram:Controlled Environment – Scripted Matrix Call-out TEST 1: Lighting Variation Effect
Block Diagram:Controlled Environment – Scripted Matrix Call-out TEST 1: Lighting Variation Effect (Continuation)
Block Diagram:Controlled Environment – Scripted Matrix Call-out TEST 2: External Facial Accessories Variation Effect
Block Diagram:Controlled Environment – Scripted Matrix Call-out TEST 3: Facial Change and Facial Emotions Variation Effect
Block Diagram:Laptop Temporary Setup & Training (CogniSight Control Panel)
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 (in-progress). • Phase 2 • With lesson learned in Phase 1: Will implement a controlled-group “open environment” characterization/testing of the device (more elaboration is just a sec). • Phase 3 • Verification and “variable-environment” testing of the controlled-group (8 individuals) to the general population False-Positive • Control group (thru external facial manipulation) to deceive & create “Positive Unknown” identification
Phase 1: Results • Result Discussion: • Lighting Variation Effects • External Facial Accessories Variations Effect • Facial Changes Effects • Facial Expression Effects
Phase 1: Lesson Learned • Perform training with “sufficient lighting” • “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.
What’s next?Phase 2 & Phase 3 • Phase 2 • With lesson learned in Phase 1: Will implement a controlled-group “open environment” characterization/testing of the device (more elaboration is just a sec). • Concurrently, research cause for the • CogniMem to “freeze” • Uncontrolled neuron assignment • USB port assignment erratic
What’s next?Phase 2 & Phase 3 • Phase 3 • Verification and “variable-environment” testing of the controlled-group (8 individuals) to the campus general population False-Positive • Control group (thru external & facial manipulation) to deceive & create “Positive Unknown” identification
Problems (Yes, we have them): • Hardware & Software • CogniMem to become unresponsive • Uncontrolled neuron assignments (without any keyboard or mouse activity); normally happens right after the CogniMem device becomes unresponsive. • USB port assignment erratic
End of Semester Project Goals: Our projected goals are to: • 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.