This proved that depth perception is a neurological process. Julesz used a computer to create a stereo pair of random-dot images which, when viewed under a stereoscope, caused the brain to see 3D shapes. At the time, many vision scientists still thought that depth perception occurred in the eye itself, whereas now it is known to be a complex neurological process. In 1959, Bela Julesz, a vision scientist, psychologist, and MacArthur Fellow, discovered the random dot stereogram while working at Bell Laboratories on recognizing camouflaged objects from aerial pictures taken by spy planes. This is the basis of wallpaper-style autostereograms (also known as single-image stereograms). Brewster noticed that staring at repeated patterns in wallpapers could trick the brain into matching pairs of them and thus causing the brain to perceive a virtual plane behind the walls. In 1838, the British scientist Charles Wheatstone published an explanation of binocular vision (binocular depth perception) which had led him to make stereoscopic drawings and to construct a stereoscope based on a combination of mirrors to allow a person to see 3D images from two 2D pictures ( stereograms).īetween 18, David Brewster, a Scottish scientist, improved the Wheatstone stereoscope by using lenses instead of mirrors, thus reducing the size of the contraption. Wall-eyed viewing requires that the two eyes adopt a relatively divergent angle, while cross-eyed viewing requires a relatively convergent angle. Most autostereograms are designed to be viewed in only one way, which is usually wall-eyed. There are two ways an autostereogram can be viewed: wall-eyed and cross-eyed. Usually, a hidden 3D scene emerges when the image is viewed with proper viewing technique. In this type of autostereogram, every pixel in the image is computed from a pattern strip and a depth map. The Magic Eye series of books features another type of autostereogram called a random dot autostereogram. When viewed with proper convergence, the repeating patterns appear to float in the air above the background. The simplest type of autostereogram consists of horizontally repeating patterns and is known as a wallpaper autostereogram. In order to perceive 3D shapes in these autostereograms, the brain must overcome the normally automatic coordination between focusing and convergence. Click on thumbnail to see full-size image.Īn autostereogram is a single-image stereogram (SIS), designed to trick the human brain into perceiving a three- dimensional (3D) scene in a two-dimensional image. Clear any blurriness but maintain the triplet to see a shark emerge from the background dots in vivid 3D.A random dot autostereogram encodes a 3D scene which can be "seen" with proper viewing technique. Converge or diverge the eyes so as to see a triplet of three black dots. The "rds depth mask" notebook creates more advanced autostereograms. Clear any blurriness but maintain the triplet to see a rectangle emerge from the background dots in vivid 3D. Converge or diverge the eyes so as to see a triplet of three red dots. The "rds simple" notebook creates basic dual image autostereograms. The project should port pretty easily to python 3 as long as you change the "xrange" keywords to "range" and other such minor changes Examples Matplotlib (but only if you want to plot stereograms inside of your iPython notebooks).If you have any questions, contact me at Dependencies I am actively experimenting with the code so that I can better understand how stereograms work. I emphasize that this is a work in progress. The notebook which takes depth masks was inspired by code from synesthesiam For a good intro to stereograms, check out Wikipedia or Gary Beene's personal website Originally built as a supplement to my article Depth perception: more than meets the eye DescriptionĪ set of ipython notebooks for making autostereogram demos and generally exploring their properties. Code for playing with random dot stereograms.
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