Democratizing Optometric Care: A Vision-Based, Data-Driven Approach to Automatic Refractive Error Measurement for Vision Screening

Tiffany C.K. Kwok, Naomi C.M. Shum, Grace Ngai, Hong Va Leong, Grace Amy Tseng, Hoi Yi Choi, Ka Yan Mak, Chi Wai Do

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

3 Citations (Scopus)


We present a vision-based, data-driven approach to identifying and measuring refractive errors in human subjects with low-cost, easily available equipment and no specialist training. Vision problems, such as refractive error (e.g. nearsightedness, astigmatism, etc) are common ocular problems, which, if uncorrected, may lead to serious visual impairment. The diagnosis of such defects conventionally requires expensive specialist equipment and trained personnel, which is a barrier in many parts of the developing world. Our approach aims to democratize optometric care by utilizing the computational power inherent in consumer-grade devices and the advances made possible by multimedia computing. We present results that show our system is able to match and outperform state-of-the-art medical devices under certain conditions.
Original languageEnglish
Title of host publicationProceedings - 2015 IEEE International Symposium on Multimedia, ISM 2015
Number of pages6
ISBN (Electronic)9781509003792
Publication statusPublished - 25 Mar 2016
Event17th IEEE International Symposium on Multimedia, ISM 2015 - Miami, United States
Duration: 14 Dec 201516 Dec 2015


Conference17th IEEE International Symposium on Multimedia, ISM 2015
Country/TerritoryUnited States


  • computer-aided diagnosis
  • refractive errors
  • smartphone refraction
  • vision screening

ASJC Scopus subject areas

  • Computer Science Applications
  • Hardware and Architecture
  • Software
  • Computer Networks and Communications

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