Peripheral vision and pattern recognition: a review - strasburger - main

Peripheral_Vision.doc
Abstract
We summarize the various strands of research on peripheral vision and relate them to theories
of form perception. After a historical overview, we describe quantifications of the cortical
magnification hypothesis, including an extension of Schwartz’s cortical mapping function. The
merits of this concept are considered across a wide range of psychophysical tasks, followed by
a discussion of its limitations and the need for non-spatial scaling. We also review the
eccentricity dependence of other low-level functions including reaction time, temporal resolution
and spatial summation, as well as perimetric methods. A central topic is then the recognition of
characters in peripheral vision, both at low and high levels of contrast, and the impact of
surrounding contours known as crowding. We demonstrate how Bouma’s law, specifying the
critical distance for the onset of crowding, can be stated in terms of the retino-cortical mapping.
The recognition of more complex stimuli, like textures, faces and scenes reveals a substantial
impact of mid-level vision and cognitive factors. We further consider eccentricity-dependent
limitations of learning, both at the level of perceptual learning and pattern category learning.
Generic limitations of extrafoveal vision are observed for the latter in categorization tasks
involving multiple stimulus classes. Finally, models of peripheral form vision are discussed. We
report that peripheral vision is limited with regard to pattern categorization by a distinctly lower
representational complexity and processing speed. Taken together, the limitations of cognitive
processing in peripheral vision appear to be as significant as those imposed on low-level
functions and by way of crowding.
Keywords: Peripheral vision, visual field, acuity, contrast sensitivity, temporal resolution,
crowding effect, perceptual learning, computational models, categorization, object recognition,
faces, facial expression, natural scenes, scene gist, texture, contour, learning, perceptual
learning, category learning, generalization, invariance, translation invariance, shift invariance,
representational complexity.
1. Introduction
The driver of a car traveling at high speed, a shy person avoiding to directly look at the object of
her or his interest, a patient suffering from age-related macular degeneration, they all face the
problem of getting the most out of seeing sidelong. It is commonly thought that blurriness of
vision is the main characteristic of that condition. Yet Lettvin (1976) picked up the thread where
Aubert and Foerster (1857) had left it when he insisted that any theory of peripheral vision
exclusively based on the assumption of blurriness is bound to fail: ”When I look at something it
is as if a pointer extends from my eye to an object. The ‘pointer’ is my gaze, and what it touches
I see most clearly. Things are less distinct as they lie farther from my gaze. It is not as if these
things go out of focus – but rather it’s as if somehow they lose the quality of form” (Lettvin,
1976, p. 10, cf. Figure 1).
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