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New Tool 'Visual Anagrams' Revolutionizes Study of Human Visual Perception

Meet 'visual anagrams', a groundbreaking tool that's transforming how we study human visual perception. By isolating specific visual properties, it's opening doors to new insights into our brains.

Here this picture is an animated image, in which we can see robots present and we can also see some...
Here this picture is an animated image, in which we can see robots present and we can also see some jets flying in the air and we can see sun and clouds in the sky and we can also see trees and mountains present.

New Tool 'Visual Anagrams' Revolutionizes Study of Human Visual Perception

Scientists have developed a new tool to study human visual perception: 'visual anagrams'. These AI-generated images appear different when rotated, revealing unexpected objects or scenes. The team behind this innovation hails from Johns Hopkins University's Perception & Mind Lab, with support from the National Science Foundation.

Visual anagrams are images composed of the exact same pixels, but they show different objects or scenes when rotated. This unique property allows researchers to isolate and study specific visual properties, like size, without the distraction of varying shapes, colors, or other factors. The team, led by researchers from the Max Planck Institute for Biological Cybernetics, published their work in Current Biology.

In initial experiments, visual anagrams confirmed classic real-world size effects. People preferred images to be depicted in ways that match their real-world size, even when the objects were rotated versions of the same image. This suggests that our brains process visual information in a consistent manner, regardless of the image's orientation. Future applications of visual anagrams include studying animate and inanimate objects, and other psychological and neuroscience experiments.

Visual anagrams, created by a team from Johns Hopkins University, offer a novel way to study human visual perception. By isolating specific visual properties, they help advance our understanding of how the brain processes visual information. The potential applications of this technology are vast, promising to enhance our knowledge of perception, cognition, and neuroscience.

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