Autostereogram

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An autostereogram is a single image stereogram (SIS), designed to create the visual illusion of a three-dimensional (3D) scene from a two-dimensional image. To view the 3D shape in this autostereograms, one must overcome the automatic coordination between accommodation (focus) and horizontal vergence (the corner of a person's eye). Illusion is one of depth perception and involves stereopsis: a deep perception arising from different perspectives each eye has a three-dimensional scene, called a binocular parallax.

The simplest type of autostereogram consists of a repeating pattern horizontally (often separating the image) and is known as a wallpaper autostereogram. When viewed with proper convergence, repetitive patterns appear to float above or below the background. The famous Magic Eye books feature another type of autostereogram called random dot autostereogram. One such autostereogram is illustrated on the right. In this type of autostereogram, each pixel in the image is calculated from the pattern strip and depth map. Hidden 3D scenes appear when images are viewed with correct convergence.

Autostereograms are similar to normal stereograms unless they are viewed without a stereoscope. Stereoscopes present 2D images of the same object from slightly different angles to the left eye and the right eye, allowing us to reconstruct the original object through a binocular difference. When viewed with proper vergence, the autostereogram does the same, binocular differences that exist in the adjacent part of the repeating 2D pattern.

There are two ways autostereogram can be seen: eyed and squint . Most autostereograms (including those in this article) are designed to be viewed in only one way, which is usually cross-eyed. Eye-eyed sightings require that both eyes adopt a relatively parallel angle, while cross-eyed eyes require a relatively convergent angle. An image that is designed to be viewed with a squinty eye when viewed correctly will appear out of the background, while it is seen that the juling will instead appear as a background background and may be difficult to fully focus.

Video Autostereogram

History

In 1838, British scientist Charles Wheatstone published an explanation of stereopsis (the perception of binocular depth) arising from the difference in the horizontal position of the image in two eyes. He supports his explanation by showing images with such horizontal differences, stereograms, separately to the left and right eye through a stereoscope he finds based on a mirror. When people look at these flat two-dimensional images, they experience the illusion of three-dimensional depth.

Between 1849 and 1850, David Brewster, a Scottish scientist, enhanced the Wheatstone stereoscope by using a lens instead of a mirror, reducing the size of the device.

Brewster also found "wallpaper effect". He noticed that staring at repetitive patterns in the wallpaper could trick the brain into matching pairs as it comes from the same virtual object in the virtual field behind the wall. This is the basis of "autostereograms" style wallpaper (also known as stereograms one image).

In 1851 H.W. Dove describes "cross-eyed view as a stereoscope" with a pair of standard stereoscopic images.

In 1939 Boris Kompaneysky published the first random dot stereogram containing the image of Venus's face, which was meant to be seen with the device.

In 1959, Bela Julesz, a vision scientist, psychologist and MacArthur Fellow, invented a random dot stereogram while working at Bell Laboratories to recognize objects disguised from aerial photographs taken by spy planes. At that time, many vision scientists still thought that depth perception occurred in the eye itself, whereas today it is known as a complex neurological process. Julesz uses a computer to create a pair of random-image stereo points that, when viewed under a stereoscope, cause the brain to see 3D shapes. This proves that depth perception is a neurological process.

Japanese designer Masayuki Ito, following Julesz, created a single image stereogram in 1970 and Swiss painter Alfons Schilling created a handmade single-handed stereogram in 1974, after creating more than one audience and meeting Julesz. Having experience with stereo imaging in holography, lenticular photography, and vectography, he developed a random-point method based on a close-range vertical line in parallax.

In 1979, Christopher Tyler of the Smith-Kettlewell Institute, a student of Julesz and a visual psychophysicist, combined the theory behind stereograms of single-wallpaper images and random-point stereograms (Julesz and Schilling's work) to create the first black-and-black color. white "random-dot autostereogram" (also known as single-image random-dot stereogram) with the help of computer programmer Maureen Clarke using Apple II and BASIC. This type of autostereogram allows one to view 3D shapes from a single 2D image without the aid of optical equipment. In 1991 computer programmer Tom Baccei and artist Cheri Smith created the first random-dot color autostereogram, which was later marketed as the Magic Eye .

A computer procedure that extracts the hidden geometry of the autostereogram image depicted by Ron Kimmel. In addition to the classic stereo it adds smoothness as an important assumption in surface reconstruction.

Maps Autostereogram

How it works

Simple wallpapers

Stereopsis, or stereo vision, is a visual mixture of two similar but not identical images together, producing a visual perception of solidity and depth. In the human brain, stereopsis is produced from a complex mechanism that forms a three-dimensional impression by matching each dot (or set of points) in the view of one eye with the equivalent point (or set of dots) in the other eye view. By using binocular differences, the brain gets the position of the points within the unintelligible z -axis (depth).

When the brain is presented with repetitive patterns such as wallpaper, it has difficulty matching the second eye view accurately. By looking at a pattern that repeats horizontally, but focusing both eyes on the point behind the pattern, it is possible to trick the brain to match one element of the pattern, as seen by the left eye, with other (similar) elements, in addition to the first, such as which is visible to the right eye. With a distinctive cross-eyed look, it gives the illusion of a plane with the same pattern but is located behind the actual wall. The distance at which the plane is behind the wall depends only on the distance between the identical elements.

Autostereograms uses depth dependence on distance to create three-dimensional images. If, in some areas of the drawing, the pattern is repeated at a smaller distance, the area will appear closer than the background area. If the repeating distance is longer in some areas, then the area will appear farther (like a hole in the plane).

People who can never see 3D forms hidden inside the autostereogram find it difficult to understand statements such as, "3D images will only pop out of the background, after you have stared at the image long enough", or "3D objects will only appear from the background". It helps to illustrate how 3D images "appear" from the background from a second audience perspective. If the virtual 3D object that is reconstructed by the autostereogram viewer's brain is the real object, the second viewer observing the scene from the side will see these objects floating in the air above the background image.

The 3D effect in the autostereogram example is created by repeating the tiger-rider icon every 140 pixels in the background field, the sharper's icon every 130 pixels in the second field, and the tiger icon every 120 pixels in the highest field. The closer a set of icons is packed horizontally, the higher they are lifted from the background field. This recurring distance is referred to as the depth value or z -ax of a particular pattern in the autostereogram. The depth value is also known as the Z-buffer value.

The brain is capable of almost instantly matching hundreds of patterns that are repeated at different intervals to create the correct depth information for each pattern. An autostereogram can contain about 50 tigers of varying sizes, repeated at different intervals against complex and repetitive backgrounds. However, regardless of the chaotic arrangement pattern, the brain is able to place every tiger icon at the proper depth.

Depth map

Autostereograms in which patterns in certain rows are repeated horizontally with the same distance can be read either cross-eye or squint. In such autostereograms, the two types of readings will produce similar depth interpretations, with the exception that the cross-eyed reading reverses the depth (the ever emerging image is pushed).

However, consecutive icons do not need to be set at the same interval. An autostereogram with various intervals between icons in one line presents these icons in different depth fields to the viewer. The depth for each icon is calculated from the distance between it and its neighbors on the left. This type of autostereograms is designed to be read in only one way, either cross-eyed or squinty. All autostereograms in this article are coded to look cross-eyed, unless specifically marked otherwise. An autosteogram encoded to see with eye view will produce an upside pattern when viewed with a squint eye, and opposite to an opponent. Most Magic Eye images are also designed to be seen with eyes looking up.

The depth-edged map of the autostereogram example to the right encodes 3 planes across x -axis. The background field is on the left side of the image. The highest field is shown on the right side of the image. There's a narrow middle plane in the middle of x -axis. Starting with a background field where icons are spaced at 140 pixels, one can raise a particular icon by sliding a number of pixels to the left. For example, a center plane is created by sliding the 10 pixel icon to the left, effectively creating a distance of 130 pixels. The brain does not rely on intelligible icons that represent objects or concepts. In this autostereogram, the patterns become smaller and smaller under y -axis, until they look like random points. The brain is still able to match this random point pattern.

The relationship of the distance between the pixels and the pair in the left-handed pattern can be expressed in the depth map . The depth map is just a grayscale image representing the distance between the pixel and the left counterpart using the grayscale value between black and white. By convention, the closer the distance, the lighter the color.

Using this convention, the gray depth maps for autostereogram samples can be made with black, gray and white shifts that represent 0 pixels, 10 pixels and 20 pixels, respectively as shown in the gray autostereogram example. The depth map is the key to making random-dot autostereogram.

Random-dots

The computer program can take a deep map and draw the accompanying pattern to produce an autostereogram. The program crops the pattern image horizontally to cover an area whose size is identical to the depth map. Conceptually, on each pixel in the output image, the program looks for the grayscale value of the equivalent pixels in the depth map image, and uses this value to determine the number of horizontal shifts required for the pixels.

One way to achieve this is to make the program scan each line in pixel by pixel output image from left to right. It was the first series seed of successive pixels of the pattern image. Then consult the depth map to take the appropriate shift value for the next pixel. For each pixel, it reduces the shift from the width of the pattern image to reach the repetition interval. It uses this repeat interval to search for the opponent's pixel color on the left and uses its color as the new pixel color itself.

Unlike the simple depth fields created by simple wallpaper autostereograms, subtle changes in the distances determined by depth maps can create the illusion of fine gradients in the distance. This is possible because the grayscale depth map allows individual pixels to be placed on one of the 2 aircraft depths ⁿ , where n is the number of bits used by each pixels in depth map. In practice, the total number of depth fields is determined by the number of pixels used for the width of the pattern image. Each grayscale value must be translated into pixel space to shift pixels in the final autostereogram. Consequently, the number of depth fields should be less than the width of the pattern.

The fine-tuned gradient requires a more complex pattern image than the standard repetition pattern wallpaper, so typically a pattern consisting of repeated random points is used. When the autostereogram is viewed with the proper display technique, a hidden 3D scene appears. Autostereograms of this form are known as Random Dot Autostereograms.

Fine gradients can also be achieved with understandable patterns, assuming that the pattern is quite complex and has no large, horizontal, monotonic fillings. A large area painted in monotonous colors without discoloration and brightness does not allow pixel shifts, as the result of a horizontal shift is identical to the original patch. The following shark depth maps with fine gradients produce perfectly readable autostereograms, although 2D images contain small monotonic areas; the brain is able to recognize these small gaps and fill the void (illusion contour). While understandable, repetitive patterns are used instead of random points, this type of autostereogram is still known by many as the Random Dot Autostereogram, since it is created using the same process.

Animated

When a series of autostereograms are shown one by one, in the same way as moving images are displayed, the brain senses an autostereogram animation. If all autostereograms in the animation are generated using the same background pattern, it is often possible to see the faint lines of parts of 3D objects moving in the 2D autostereogram image without a bulging glance; the moving pixels of a moving object can be clearly distinguished from the static background field. To eliminate these side effects, autostereograms animations often use a shifted background to disguise moving parts.

When repetitive patterns are regularly seen on a CRT monitor as if it were a wallpaper autostereogram, it is usually possible to see ripple depth. This can also be seen in the background for static, random-dot autostereogram. This is caused by a sideways shift in the image due to a small change in the sensitivity of the deflection (linearity) of the line scan, which is then interpreted as depth. This effect is clearly visible on the left edge of the screen where scan speed still persists after the flyback phase. On the TFT LCD, which works differently, this does not happen and the effect does not exist. Higher quality CRT displays also have better linearity and show less or no effect.

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Mechanisms to view

Many suggestions are there about looking at the three-dimensional images that are meant in the autostereogram. While some people can quickly see 3D images in an autostereogram with little effort, others must learn to train their eyes to separate the convergence of the eye from the lens focus.

Not everyone can see 3D illusions in autostereograms. Because autostereograms are built on stereo vision, people with visual impairments, even those affecting only one eye, can not see three-dimensional images.

People with amblyopia (also known as lazy eyes) can not see three-dimensional images. Children with poor or dysfunctional vision during childhood critical periods may grow stereoblind, as their brains are not stimulated by stereo images during critical periods. If such vision problems are not corrected in early childhood, the damage becomes permanent and adults will never be able to see autostereograms. It is estimated that about 1 percent to 5 percent of the population is affected by amblyopia.

3D Perception

The perception of the depth results from many monocular visual clues and binoculars. For objects relatively close to the eye, binocular vision plays an important role in deep perception. Sighted binoculars allow the brain to create a single Cyclopean image and to attach the depth level to each point inside.

The brain uses coordinate shifts (also known as parallaxes) of objects that are suitable for identifying the depth of these objects. The depth level of each point in the composite image can be represented by the grayscale pixel in 2D images, for the benefit of the reader. The closer the point comes to the brain, the brighter it is painted. Thus, the way the brain perceives depth using binocular vision can be captured by a depth map (Cyclopean picture) painted based on coordinate shifts.

Eyes operate like photographic cameras. It has an adjustable iris that can open (or close) to allow more (or less) light into the eye. As with any camera except for pinhole cameras, the camera needs to focus the rays of incoming light through the iris (aperture in the camera) so that it focuses on one point on the retina to produce a sharp image. The eye reaches this goal by adjusting the lens behind the cornea to refract light appropriately.

Parallax based stereo vision allows the brain to calculate object depth relative to the convergence point. This is the convergence angle that gives the brain the absolute reference depth value to a point of convergence from which the absolute depth of all other objects can be inferred.

3D perception simulation

The eye is usually focused and fused at the same distance in a process known as accommodative convergence. That is, when looking at a distant object, the brain automatically flattens the lens and rotates the two eyeballs to be seen with the eye looking up. It is possible to train the brain to separate these two operations. This separation has no useful purpose in everyday life, because it prevents the brain from interpreting objects in a coherent way. To view man-made images such as autostereograms where patterns are repeated horizontally, however, the separation of focus from convergence is essential.

By focusing the lens on the nearest autostereogram where the pattern is repeated and by uniting the eyeball at a point further behind the autostereogram image, one can trick the brain to see 3D images. If the pattern received by both eyes is quite similar, the brain will assume both of these patterns fit and treat them as coming from the same imaginary object. This type of visualization is known as sight-eyed because the eyeball adopts convergence in the far field, although the autostereogram image is actually closer to the eye. Since two eyeballs are assembled on a farther plane, the perceived location of the imaginary object is behind the autostereogram. The imaginary object also appears larger than the pattern on the autostereogram due to foreshortening.

The following autostereogram shows three rows of repeating patterns. Each pattern is repeated at different intervals to place it in different depth fields. Two non-repetitive rows can be used to verify the correct view. When the autostereogram is correctly interpreted by the brain using a sighted eye, and one stares at a dolphin in the middle of a visual field, the brain will see two sets of twinkling lines, as a result of binocular competition.

While there are six dolphin patterns in the autostereogram, the brain should see seven "clear" dolphins in the autostereogram field. This is a side effect of a pair of similar patterns by the brain. There are five pairs of dolphin patterns in this picture. This allows the brain to create five dolphins. The leftmost pattern and the rightmost pattern by themselves do not have a spouse, but the brain tries to assimilate these two patterns into the adjacent field of adjacent dolphins despite a binocular competition. As a result, there are seven clear dolphins, with the leftmost and the far right appearing with little flicker, no different from the two sets of blinking lines observed when one stares at the obviously fourth dolphin.

Due to foreshortening, the difference in convergence required to see repeated patterns in various planes causes the brain to connect different sizes to patterns with identical 2D sizes. In the autostereogram are three rows of cubes, while all cubes have the same physical 2D dimension, which in the top row appears larger, as they are considered farther than the cubes on the second and third rows.

Viewing techniques

If a person has two eyes, healthy vision, and no neurological conditions that prevent depth perception then one is able to learn to see images in autostereograms. "Like learning to ride a bicycle or swim, some take it straight away, while others are more difficult."

As with photography cameras, it's easier to keep the eye focused on objects when there is intense ambient light. With intense lighting, the eyes can constrict the pupils, but allow sufficient light to reach the retina. The more the eye resembles a pinhole camera, the less it depends on focusing through the lens. In other words, a degree of separation between focus and convergence is necessary to visualize a reduced autostereogram. This reduces the tension in the brain. Therefore, it may be easier for autostereogram viewers first to "see" their first 3D image if they try this achievement with bright lighting.

Vergen controls are important for viewing 3D images. Thus, it may help to concentrate on convergent/twisted eyes to shift images that reach both eyes, instead of trying to see clear, focused images. Although the lens adjusts reflexively to produce clear and focused images, voluntary control of this process is possible. The audience turns instead between convergent and distorted eyes, in the process of seeing a "double image" usually seen when someone is drunk or drunk. Eventually the brain will successfully match a pair of patterns reported by both eyes and lock to a certain convergence level. The brain will also adjust the eyepiece to get a clear picture of the matching pair. Once this is done, the image around the matching pattern quickly becomes apparent as the brain matches the additional pattern using approximately the same convergence rate.

When someone moves one's attention from one depth field to another (for example, from the top of the chessboard to the bottom row), both eyes need to adjust their convergence to match the new recurring pattern interval. If the rate of convergence change is too high during this shift, sometimes the brain can lose the difficult decoupling between focus and convergence. For the first time viewer, therefore, it may be easier to see the autostereogram, if two eyes practice convergence exercises on the autostereogram where the depth of the pattern in a particular row remains constant.

In a random point autostereogram, a 3D image is usually displayed in the center of the autostereogram with a depth background field (see shark autostereogram). It can help to establish the right convergence first by looking at either the top or the bottom of the autostereogram, where the pattern is usually repeated at a constant interval. Once the brain locks into the depth of the background field, it has a reference convergence level from which it can then match patterns at different depth levels in the middle of the image.

The majority of autostereograms, including those in this article, are designed for different views (wall-eyed). One way to help the brain concentrate on divergence instead of focus is by holding the image in front of the face, with the nose touching the image. With images so close to their eyes, most people can not focus on the image. The brain may give up trying to move the eye muscles to get a clear picture. If someone pulls the image away from the face, while refraining from focus or rolling eyes, at some point the brain will lock into a pair of patterns as the distance between them corresponds to the current convergence level of the two eyeballs.

Another way is to stare at the object behind the image in an effort to build the right divergence, while keeping the part of the vision fixed on the image to convince the brain to focus on the image. The modified method has a viewer that focuses on its reflection on the reflective surface of the image, which the brain feels placed twice as far away from the image itself. This can help persuade the brain to adopt the necessary differences while focusing on nearby images.

Source of the article : Wikipedia