Peripheral vision and pattern recognition: a review.

By Hans Strasburger, Ingo Rentschler, Martin Jüttner. Journal of Vision, 2011

974 citations recorded by the source corpus.

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 retinocortical 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.

Subfields: Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/b718f4166c7b835d6fef923937b7a6fc68355961

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Citations in the corpus

AutoFocus: Efficient Multi-Scale Inference (2018, background): “Our lower resolution peripheral vision has a ﬁeld of view of 110 degrees [57].”
DAE-GAN: Dynamic Aspect-aware GAN for Text-to-Image Synthesis (2021, background): “Researchers have already demonstrated that human eyes have central vision and peripheral vision [1, 34, 25].”
Computational role of eccentricity dependent cortical magnification (2014, neutral): “An example of an empirical function (Cowey and Rolls, 1974 [4], described in [16]) isM−1 = M(1+ax), whereM is the cortical magnification factor, M and a are constants and x is eccentricity.”