A compressed sensing model of peripheral vision

Jens Hocke; Michael Dorr; Erhardt Barth

doi:10.1117/12.908664

A compressed sensing model of peripheral vision

Jens Hocke, Michael Dorr, Erhardt Barth

Institute of Neuro- and Bioinformatics

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.

Original language	English
Title of host publication	Human Vision and Electronic Imaging XVII
Editors	Bernice E. Rogowitz, Thrasyvoulos N. Pappas, Huib de Ridder
Number of pages	7
Volume	8291
Publisher	SPIE
Publication date	21.02.2012
Article number	82910Z
ISBN (Print)	9780819489388
DOIs	https://doi.org/10.1117/12.908664
Publication status	Published - 21.02.2012
Event	Human Vision and Electronic Imaging 2012 - San Francisco, United States Duration: 23.01.2012 → 26.01.2012 http://users.eecs.northwestern.edu/~pappas/hvei/past.html

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1117/12.908664

Cite this

@inproceedings{26d1d0b90b8f4fc792966736ce7be2dc,

title = "A compressed sensing model of peripheral vision",

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.",

author = "Jens Hocke and Michael Dorr and Erhardt Barth",

year = "2012",

month = feb,

day = "21",

doi = "10.1117/12.908664",

language = "English",

isbn = "9780819489388 ",

volume = "8291",

series = "Proceedings of SPIE",

publisher = "SPIE",

editor = "Rogowitz, {Bernice E. } and Pappas, {Thrasyvoulos N. } and {de Ridder}, Huib",

booktitle = "Human Vision and Electronic Imaging XVII",

note = "Human Vision and Electronic Imaging 2012 ; Conference date: 23-01-2012 Through 26-01-2012",

url = "http://users.eecs.northwestern.edu/~pappas/hvei/past.html",

}

A compressed sensing model of peripheral vision. / Hocke, Jens; Dorr, Michael; Barth, Erhardt.
Human Vision and Electronic Imaging XVII. ed. / Bernice E. Rogowitz; Thrasyvoulos N. Pappas; Huib de Ridder. Vol. 8291 SPIE, 2012. 82910Z (Proceedings of SPIE; Vol. 8291).

Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

TY - GEN

T1 - A compressed sensing model of peripheral vision

AU - Hocke, Jens

AU - Dorr, Michael

AU - Barth, Erhardt

PY - 2012/2/21

Y1 - 2012/2/21

N2 - 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.

AB - 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.

U2 - 10.1117/12.908664

DO - 10.1117/12.908664

M3 - Conference contribution

SN - 9780819489388

VL - 8291

T3 - Proceedings of SPIE

BT - Human Vision and Electronic Imaging XVII

A2 - Rogowitz, Bernice E.

A2 - Pappas, Thrasyvoulos N.

A2 - de Ridder, Huib

PB - SPIE

T2 - Human Vision and Electronic Imaging 2012

Y2 - 23 January 2012 through 26 January 2012

ER -

A compressed sensing model of peripheral vision

Abstract

UN SDGs

Access to Document

Fingerprint

Cite this