Purchase this article with an account.
Anke Cajar, Ralf Engbert, Jochen Laubrock; How spatial frequencies and color drive object search in real-world scenes: A new eye-movement corpus. Journal of Vision 2020;20(7):8. doi: https://doi.org/10.1167/jov.20.7.8.
Download citation file:
© ARVO (1962-2015); The Authors (2016-present)
When studying how people search for objects in scenes, the inhomogeneity of the visual field is often ignored. Due to physiological limitations, peripheral vision is blurred and mainly uses coarse-grained information (i.e., low spatial frequencies) for selecting saccade targets, whereas high-acuity central vision uses fine-grained information (i.e., high spatial frequencies) for analysis of details. Here we investigated how spatial frequencies and color affect object search in real-world scenes. Using gaze-contingent filters, we attenuated high or low frequencies in central or peripheral vision while viewers searched color or grayscale scenes. Results showed that peripheral filters and central high-pass filters hardly affected search accuracy, whereas accuracy dropped drastically with central low-pass filters. Peripheral filtering increased the time to localize the target by decreasing saccade amplitudes and increasing number and duration of fixations. The use of coarse-grained information in the periphery was limited to color scenes. Central filtering increased the time to verify target identity instead, especially with low-pass filters. We conclude that peripheral vision is critical for object localization and central vision is critical for object identification. Visual guidance during peripheral object localization is dominated by low-frequency color information, whereas high-frequency information, relatively independent of color, is most important for object identification in central vision.
This PDF is available to Subscribers Only