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Proceedings Paper • Open Access

What is stereoscopic vision good for?
Author(s): Jenny C. A. Read

Paper Abstract

Stereo vision is a resource-intensive process. Nevertheless, it has evolved in many animals including mammals, birds, amphibians and insects. It must therefore convey significant fitness benefits. It is often assumed that the main benefit is improved accuracy of depth judgments, but camouflage breaking may be as important, particularly in predatory animals. In humans, for the last 150 years, stereo vision has been turned to a new use: helping us reproduce visual reality for artistic purposes. By recreating the different views of a scene seen by the two eyes, stereo achieves unprecedented levels of realism. However, it also has some unexpected effects on viewer experience. The disruption of established mechanisms for interpreting pictures may be one reason why some viewers find stereoscopic content disturbing. Stereo vision also has uses in ophthalmology. Clinical stereoacuity tests are used in the management of conditions such as strabismus and amblyopia as well as vision screening. Stereoacuity can reveal the effectiveness of therapy and even predict long-term outcomes post surgery. Yet current clinical stereo tests fall far short of the accuracy and precision achievable in the lab. At Newcastle University, we are exploiting the recent availability of autostereo 3D tablet computers to design a clinical stereotest app in the form of a game suitable for young children. Our goal is to enable quick, accurate and precise stereoacuity measures which will enable clinicians to obtain better outcomes for children with visual disorders.

Paper Details

Date Published: 17 March 2015
PDF: 13 pages
Proc. SPIE 9391, Stereoscopic Displays and Applications XXVI, 93910N (17 March 2015); doi: 10.1117/12.2184988
Show Author Affiliations
Jenny C. A. Read, Newcastle Univ. (United Kingdom)


Published in SPIE Proceedings Vol. 9391:
Stereoscopic Displays and Applications XXVI
Nicolas S. Holliman; Andrew J. Woods; Gregg E. Favalora; Takashi Kawai, Editor(s)

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