
Proceedings Paper
A compressed sensing model of crowding in peripheral visionFormat | Member Price | Non-Member Price |
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Paper Abstract
We here model peripheral vision in a compressed sensing framework as a strategy of optimally guessing what
stimulus corresponds to a sparsely encoded peripheral representation, and find that typical letter-crowding effects
naturally arise from this strategy. The model is simple as it consists of only two convergence stages. We apply
the model to the problem of crowding effects in reading. First, we show a few instructive examples of letter
images that were reconstructed from encodings with different convergence rates. Then, we present an initial
analysis of how the choice of model parameters affects the distortion of isolated and flanked letters.
Paper Details
Date Published: 20 February 2012
PDF: 7 pages
Proc. SPIE 8291, Human Vision and Electronic Imaging XVII, 82910Z (20 February 2012); doi: 10.1117/12.908664
Published in SPIE Proceedings Vol. 8291:
Human Vision and Electronic Imaging XVII
Bernice E. Rogowitz; Thrasyvoulos N. Pappas; Huib de Ridder, Editor(s)
PDF: 7 pages
Proc. SPIE 8291, Human Vision and Electronic Imaging XVII, 82910Z (20 February 2012); doi: 10.1117/12.908664
Show Author Affiliations
Jens Hocke, Univ. zu Lübeck (Germany)
Michael Dorr, Schepens Eye Research Institute (United States)
Michael Dorr, Schepens Eye Research Institute (United States)
Erhardt Barth, Univ. zu Lübeck (Germany)
Published in SPIE Proceedings Vol. 8291:
Human Vision and Electronic Imaging XVII
Bernice E. Rogowitz; Thrasyvoulos N. Pappas; Huib de Ridder, Editor(s)
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