Facial Recognition Using Simulated Prosthetic Pixelized Vision

Abstract
RESULTS. Discrimination speed and performance were influ- enced 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 accu- racy 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 dur- ing high-contrast trials, and a more subtle practice effect on timing was evident during subsequent low-contrast trials. CONCLUSIONS. These findings suggest that reliable face recogni- tion with crude pixelized grids can be learned and may be possible, even with a crude visual prosthesis. (Invest Ophthal- mol Vis Sci. 2003;44:5035-5042) DOI:10.1167/iovs.03-0341 I n the United States, at least 1.3 million people (0.5%) are legally blind. In 2001, the American Foundation for the Blind estimated that 260,000 Americans have vision that is clinically measured as light perception vision or less, and roughly half of