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Amy A. Kalia, Paul R. Schrater, Gordon E. Legge, Christopher S. Kallie; Estimating absolute distances with blurred vision. Journal of Vision 2008;8(6):1047. doi: 10.1167/8.6.1047.
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© ARVO (1962-2015); The Authors (2016-present)
Humans are able to accurately walk while blindfolded to the location of a previously viewed target, a paradigm called a visually-directed walking task. Task success requires accurately converting visual estimates of absolute distance into walked estimates. However, people underestimate distances when visual depth cues are severely reduced, as when targets are viewed in the dark (Ooi, Wu & He, 2001; Ooi, Wu & He, 2006). One possibility is that underestimation results from combining visual distance information with a prior bias for an upward sloping ground plane that results in perceptually shorter distances to targets (Ooi, et al., 2006). If so, then as visual information becomes unreliable, reliance on prior biases may increase resulting in greater underestimation. The current study investigated this hypothesis by blurring vision to manipulate variability in visual distance estimation. Twelve normally-sighted participants viewed targets in a hallway under three monocular viewing conditions: no blur, low blur (average Snellen acuity of 20/180), and high blur (20/675). Targets were pairs of high-intensity Light-Emitting Diodes located on the floor 3 to 11 meters from the observer. After viewing a target, participants walked to its perceived location blindfolded. Results indicated that the variability of distance estimates increased with both blur and target distance (standard deviations of participants' estimates for the 11 meter target: No Blur: 1.15 m; Low Blur: 1.78 m; High Blur: 2.32 m). Similarly, underestimation increased on average with increasing blur and distance (walked distances to the 11 meter target: No Blur: M = 9.92 m, SE = 0.25 m; Low Blur: M = 8.80 m, SE = 0.49 m; High Blur: M = 8.93 m, SE = 0.56 m). These findings show that blurred vision leads to greater variability and greater underestimation in visual estimates of distances, consistent with an increased reliance on prior biases for object distances.
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