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Subproject 3 Human-Computer Interaction for Universal Access

Subproject 3 Human-Computer Interaction for Universal Access. Subproject PI: Armando Barreto Subproject Co-PIs: Malek Adjouadi, Naphtali Rishe, Christine Lisetti Subproject Collaborators: Xudong He, Zhenyu Yang. HCI for Universal Access.

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Subproject 3 Human-Computer Interaction for Universal Access

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  1. Subproject 3 Human-Computer Interaction for Universal Access Subproject PI: Armando Barreto Subproject Co-PIs: Malek Adjouadi, Naphtali Rishe, Christine Lisetti Subproject Collaborators: Xudong He, Zhenyu Yang

  2. HCI for Universal Access • Multiple developments to enhance access to computers, particularly under challenging conditions (environment, disabilities) • “10-minute Talk” • Update regarding 3 of the developments

  3. Improving Web Browser for Blind Users through Audio-Spatialized Screen Reader TRANSCODING SERVER (proxy) Leverage our previous work on Spatialized Sound to explore a potentially better solution Spatial VBAP Text-to- Speech EFFECT

  4. Interaction Enhancement Pitch increase Pitch decrease Sound Spatialization 86% (5 col.)

  5. WAVEFRONT ABERRATION MEASUREMENT RETINAL PROJECTION (output) OBJECT (input) RETINAL PROJECTION (output) OBJECT (input) O(x,y) RD(x,y) “Display Image” Results from convolution of input with impulse response PSF POINT SPREAD FUNCTION (impulse response, H) I(x,y) I(x,y) H(x,y) O(x,y) Computer H(x,y) Pre-compensation of Computer Images for Users with Visual Aberrations WAVEFRONT ANALIZER DEPENDS ON PUPIL SIZE

  6. Pre-compensated Image on Computer Screen Original Image PD measurement User PD = Pupil Diameter W = Wavefront Aberration Function PD PRE-COMPENSATION UPDATE W Eye Gaze Tracker Dynamic Compensation(Real-time Pupil Measurement)

  7. Example with a -6 Diopter Lens (and a high-resolution camera) ORIGINAL IMAGE PRE-COMPENSATED IMAGE Viewing through Defocus Viewing through Defocus Image Blurred by -6.0D lens (defocus) Pre-compensated Image seen through the -6.0D lens

  8. Preliminary Evaluation Results • 10 subjects, (20 monocular tests). • Aberrations: • Spherical: -3.24D to -10.34D (-6.36±1.99D) • Cylindrical : -0.22D to -2.03D (-0.76±0.48D) • Eight Icons used in experiment (Copy, Document, Folder, Email, Picture, Printer, Save and Delete). 2 sizes: Small (48 Pixels side) Large (72 Pixels side) • Each eye saw 4 sets of 8 icons (random order): Original Small Large Dynamically Pre-compensated Small Large • Statistically Significant (p < 0.01) improvement by Method (better WITH PRE-COMPENSATION) • Significant (p < 0.05) size * method interaction, i.e., most helpful for small icons

  9. Multi-touch Navigation in 3D Data

  10. 2-D Gestures Used for 3-D Navigation BASIC EXAMPLES:

  11. Custom 3-D Maze for Evaluation

  12. A new generation of leadership Dr. Navarun Gupta Supported by Phase I FIU CREST Now Tenured Associate Professor And Associate Chair of EE at University of Bridgeport (CT) https://equella.bridgeport.edu/main/items/bd408fcc-1480-ba6d-098c-fbb70ca1e36e/3/

  13. A new generation of leadership Dr. Miguel Alonso Jr. Sponsored by FIU CREST Phase I and NSF GRF (MS, PhD) Now Tenured Associate Professor and Engineering & Technology Chair at Miami-Dade College (MDC: HSI … “largest institution of higher education in the United States”, 174,000 students) http://www.mdc.edu/main/about/

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