On a common circle: Natural scenes and Gestalt rules

On a common circle: Natural scenes and Gestalt rules

Laboratories of ^*Mathematical Physics and ^†Neurobiology, The Rockefeller University, 1230 York Avenue, New York, NY 10021

Communicated by A. James Hudspeth, The Rockefeller University, New York, NY (received for review October 25, 2000)

Abstract

To understand how the human visual system analyzes images, it is essential to know the structure of the visual environment. In particular, natural images display consistent statistical properties that distinguish them from random luminance distributions. We have studied the geometric regularities of oriented elements (edges or line segments) present in an ensemble of visual scenes, asking how much information the presence of a segment in a particular location of the visual scene carries about the presence of a second segment at different relative positions and orientations. We observed strong long-range correlations in the distribution of oriented segments that extend over the whole visual field. We further show that a very simple geometric rule, cocircularity, predicts the arrangement of segments in natural scenes, and that different geometrical arrangements show relevant differences in their scaling properties. Our results show similarities to geometric features of previous physiological and psychophysical studies. We discuss the implications of these findings for theories of early vision.

Footnotes

↵ ‡ Present address: Functional Neuroimaging Laboratory, Department of Psychiatry, Cornell University, 1300 York Avenue, Box 140, New York, NY 10021.
↵ § To whom reprint requests should be addressed at: The Rockefeller University, 1230 York Avenue, Box 212, New York, NY 10021-6399. E-mail: marcelo{at}zahir.rockefeller.edu.
Article published online before print: Proc. Natl. Acad. Sci. USA, 10.1073/pnas.031571498.
Article and publication date are at www.pnas.org/cgi/doi/10.1073/pnas.031571498
↵ ¶ Simoncelli, E. P. & Schwarz, O., Oral Presentation, Conference on Neural Information Processing Systems, Dec. 1–3, 1998, Denver, CO.
Abbreviation:

V1,

primary visual cortex