When an observer looks at an image, his eyes fixate on a few select points. Fixations from different observers are often consistent--observers tend to look at the same locations. We investigate how image resolution affects fixation locations and consistency across humans through an eye tracking experiment. We showed 168 natural images and 25 pink noise images at different resolutions to 64 observers. Each image was shown at eight resolutions (height between 4-512 pixels) and upsampled to 860x1024 pixels for display. The total amount of visual information available ranged from 1/8 to 16 cycles per degree respectively. We measure how well one observer's fixations predict another observer's fixations on the same image at different resolutions using the area under the receiver operating characteristic (ROC) curves as a metric. We found that: 1) Fixations from lower-resolution images can predict fixations on higher-resolution images. 2) Human fixations are biased towards the center for all resolutions and this bias is stronger at lower resolutions. 3) Human fixations become more consistent as resolution increases until around 16-64px (1/2 to 2 cycles per degree) after which consistency remains relatively constant despite the spread of fixations away from the center. 4) Fixation consistency depends on image complexity.
|Image Stimuli||300 images zip (330MB)|
|Fixation Data||zip (31.7MB)|
predictFixations.m calculates area under the ROC curve
checkFixations.m determines saccades and fixations from raw eye tracking data
This research was supported by NSF CAREER awards 0447561 and IIS 0747120. Frédo Durand acknowledges a Microsoft Research New Faculty Fellowship, a Sloan Fellowship, Royal Dutch Shell, the Quanta T-Party, and the MIT-Singapore GAMBIT lab. We thank Aude Oliva, Barbara Hidalgo-Sotelo and Krista Ehinger for their help and comments and Aude Oliva for the use of her eye tracker.