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MiYoung Kwon, Rong Liu; Compensation for blur requires an increase in field of view. Journal of Vision 2016;16(12):1178. doi: https://doi.org/10.1167/16.12.1178.
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© ARVO (1962-2015); The Authors (2016-present)
Spatial resolution is an important factor in human pattern recognition. In particular, low resolution (blur) is a defining characteristic of low vision. Blur changes image information such that fine local information is largely reduced while global or configural information (i.e., the spatial interrelationship between local features) is likely to remain intact. A possible interaction between blur and field of view comes from an interesting observation that a larger field of view is advantageous to access configural information of an object. Here, we investigated an interaction between the two by assessing field of view requirement for blurry object recognition. Eight normally-sighted subjects were asked to recognize letters and faces blurred with a low-pass filter (cycles/object cutoff) using a moving-window paradigm. Subjects viewed an object of fixed size through a gaze-contingent viewing window with varying sizes until they recognize it. Field of view requirement, quantified as the total number of "views" (i.e. repositions of the window) required for correct recognition, was obtained for three blur levels. Number of views increased as the window size decreased. More importantly, the increase in the number of views was more pronounced with increasing blur level (F(2, 98) = 21.66, p < 0.001 for letter; F(2, 98) = 12.63, p < 0.001 for face), suggesting that a larger field of view is required to recognize blurry objects of a given size. Our findings suggest that, while human observers excel at recognizing severely blurred objects, compensating for blur requires an increase in field of view, which may challenge object recognition in low vision. Thus, the interaction between blur and field of view should be considered when low vision rehabilitation or assistive aids are designed.
Meeting abstract presented at VSS 2016
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