Facial Recognition Using Simulated Prosthetic Pixelized Vision

To evaluate a model of simulated pixelized prosthetic vision using noncontiguous circular phosphenes, to test the effects of phosphene and grid parameters on facial recognition. A video headset was used to view a reference set of four faces, followed by a partially averted image of one of those face...

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Bibliographic Details
Published inInvestigative ophthalmology & visual science Vol. 44; no. 11; pp. 5035 - 5042
Main Authors Thompson, Robert W., Jr, Barnett, G. David, Humayun, Mark S, Dagnelie, Gislin
Format Journal Article
LanguageEnglish
Published Rockville, MD ARVO 01.11.2003
Association for Research in Vision and Ophtalmology
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ISSN0146-0404
1552-5783
1552-5783
DOI10.1167/iovs.03-0341

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Summary:To evaluate a model of simulated pixelized prosthetic vision using noncontiguous circular phosphenes, to test the effects of phosphene and grid parameters on facial recognition. A video headset was used to view a reference set of four faces, followed by a partially averted image of one of those faces viewed through a square pixelizing grid that contained 10x10 to 32x32 dots separated by gaps. The grid size, dot size, gap width, dot dropout rate, and gray-scale resolution were varied separately about a standard test condition, for a total of 16 conditions. All tests were first performed at 99% contrast and then repeated at 12.5% contrast. Discrimination speed and performance were influenced by all stimulus parameters. The subjects achieved highly significant facial recognition accuracy for all high-contrast tests except for grids with 70% random dot dropout and two gray levels. In low-contrast tests, significant facial recognition accuracy was achieved for all but the most adverse grid parameters: total grid area less than 17% of the target image, 70% dropout, four or fewer gray levels, and a gap of 40.5 arcmin. For difficult test conditions, a pronounced learning effect was noticed during high-contrast trials, and a more subtle practice effect on timing was evident during subsequent low-contrast trials. These findings suggest that reliable face recognition with crude pixelized grids can be learned and may be possible, even with a crude visual prosthesis.
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ISSN:0146-0404
1552-5783
1552-5783
DOI:10.1167/iovs.03-0341