Using Visual Texture for Information Display

42Citations
Citations of this article
58Readers
Mendeley users who have this article in their library.

Abstract

Results from vision research are applied to the synthesis of visual texture for the purposes of information display. The literature surveyed suggests that the human visual system processes spatial information by means of parallel arrays of neurons that can be modeled by Gabor functions. Based on the Gabor model, it is argued that the fundamental dimensions of texture for human perception are orientation, size 1995, and contrast. It is shown that there are a number of trade-offs in the density with which information can be displayed using texture. Two of these are (1) a trade-off between the size of the texture elements and the precision with which the location can be specified, and (2) the precision with which texture orientation can be specified and the precision with which texture size can be specified. Two algorithms for generating texture are included. © 1995, ACM. All rights reserved.

References Powered by Scopus

Receptive fields and functional architecture of monkey striate cortex

4792Citations
N/AReaders
Get full text

Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters

2683Citations
N/AReaders
Get full text

Application of fourier analysis to the visibility of gratings

2395Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Information Visualization: Perception for Design: Second Edition

1073Citations
N/AReaders
Get full text

Information Visualization

427Citations
N/AReaders
Get full text

Information Visualization: Perception for Design

364Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Ware, C., & Knight, W. (1995). Using Visual Texture for Information Display. ACM Transactions on Graphics (TOG), 14(1), 3–20. https://doi.org/10.1145/200972.200974

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 30

59%

Professor / Associate Prof. 9

18%

Researcher 9

18%

Lecturer / Post doc 3

6%

Readers' Discipline

Tooltip

Computer Science 35

74%

Engineering 6

13%

Psychology 4

9%

Social Sciences 2

4%

Save time finding and organizing research with Mendeley

Sign up for free