Semantic labelling to aid navigation in prosthetic vision

Lachlan Horne, Jose M. Alvarez, Chris McCarthy, Nick Barnes

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

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. Our system automatically classifies each pixel in a natural image into a semantic class, then produces an image from the induced visual percepts that highlights certain classes. This technique allows the user to clearly perceive the location of different types of objects in their field of view, and can be adapted for a range of navigation tasks.

Original languageEnglish
Title of host publication2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3379-3382
Number of pages4
ISBN (Electronic)9781424492718
DOIs
Publication statusPublished - 4 Nov 2015
Externally publishedYes
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
Duration: 25 Aug 201529 Aug 2015

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2015-November
ISSN (Print)1557-170X

Conference

Conference37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
Country/TerritoryItaly
CityMilan
Period25/08/1529/08/15

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