Semantic labelling to aid navigation in prosthetic vision.

Current and near-term implantable prosthetic vision systems offer the potential to restore some visual function, but suffer from limited resolution and dynamic range of induced visual percepts. This can make navigating complex environments difficult for users. Using semantic labelling techniques, we demonstrate that a computer system can aid in obstacle avoidance, and localizing distant objects.

Image segmentation for enhancing symbol recognition in prosthetic vision.

Current and near-term implantable prosthetic vision systems offer the potential to restore some visual function, but suffer from poor resolution and dynamic range of induced phosphenes. This can make it difficult for users of prosthetic vision systems to identify symbolic information (such as signs) except in controlled conditions. Using image segmentation techniques from computer vision, we show it is possible to improve the clarity of such symbolic information for users of prosthetic vision implants in uncontrolled conditions.

The role of vision processing in prosthetic vision.

Prosthetic vision provides vision which is reduced in resolution and dynamic range compared to normal human vision. This comes about both due to residual damage to the visual system from the condition that caused vision loss, and due to limitations of current technology. However, even with limitations, prosthetic vision may still be able to support functional performance which is sufficient for tasks which are key to restoring independent living and quality of life.