o stream as a bunch of pixels coming in from the eyes, the real challenge for the visual system is to decide which pixels belong to which objects. We wondered whether information about eye movements is used by the brain to solve this difficult problem," says Hafed, who is an NSERC ( Canada) and Sloan-Swartz post-doctoral researcher at the Salk Institute.
Krauzlis explains that the human brain recognizes objects in everyday circumstances because it is very good at filling in missing visual information. "When we see a deer partially hidden by tree trunks in a forest, we can still segment the visual scene and properly interpret the individual features and group them together into objects," he says.
However, even though recognizing that deer is effortless for us, it is not a trivial accomplishment for the brain. Teaching computers to recognize objects in real life situations has proven to be an almost insurmountable problem. Artificial intelligence researchers have spent much time and effort trying to design robots that can recognize objects in unconstrained situations, but so far, their success has been limited.
To determine whether eye movements actually help the brain recognize objects, Hafed and Krauzlis asked whether people perceived an object better when they actively moved their eyes or when they stared at a given point in space. Human subjects watched a short video that allowed them to glimpse a partially hidden chevron shape that moved in a circle.
When they kept their eyes still by fixating on a stationary spot, observers perceived only random lines moving up and down. But when they moved their eyes such that the input video streams through them were unaltered, viewers easily recognized the lines as a circling chevron.
"It turns out that eye movements not only help with image stabilization, but that this additional input also plays a fairly important role for the perception of objects in the face of
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