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Prosopagnosia

Prosopagnosia

Prosopagnosia, also known as face blindness, is the inability to recognize faces. In severe cases, individuals with prosopagnosia may not recognize close family members, including parents and spouses, by their faces. For instance, someone with prosopagnosia might walk past their child in a crowd, only realizing their mistake upon noticing their child's distinctive backpack or favorite jacket. Prosopagnosia specifically impairs facial recognition, while the recognition of other objects or...

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Updated: Mar 6, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Embedded clutter reduction and face detection algorithms for a visual prosthesis.

Derek M Rollend, Paul E Rosendall, Kevin C Wolfe

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|March 9, 2017

Summary

This summary is machine-generated.

This study presents a visual processing system for retinal prostheses, enhancing environmental perception for visually impaired individuals. The system uses image analysis to improve object recognition and autonomy, boosting the effectiveness of prosthetic devices.

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Techniques for Processing Eyes Implanted With a Retinal Prosthesis for Localized Histopathological Analysis

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Published on: August 2, 2013

Area of Science:

Biomedical Engineering
Computer Vision
Ophthalmology

Background:

Visual impairment significantly impacts independence.
Current retinal prostheses offer limited environmental perception.
Advanced image processing can enhance prosthetic functionality.

Purpose of the Study:

To develop and implement a visual processing system for retinal prostheses.
To improve environmental perception and autonomy for users of retinal implants.
To enhance object and face localization in cluttered scenes for visually impaired individuals.

Main Methods:

Image analysis techniques for visual pattern generation.
Object and face localization algorithms for cluttered environments.
Contrast enhancement strategies for the 'implanted image'.
Real-time implementation on the Argus II retinal prosthesis platform.

Main Results:

Successful development of a visual processing pipeline.
Demonstrated object and face localization capabilities.
Effective contrast enhancement strategies implemented.
Real-time system deployment on the Argus II platform.

Conclusions:

The developed visual processing system significantly improves environmental perception for retinal prosthesis users.
This technology enhances self-guidance and autonomy for individuals with visual impairments.
Advances in image processing are crucial for next-generation retinal prostheses.