One of the most remarkable achievements of perceptual systems is the stability of the perceptual world. This fact is called perceptual constancy. Under ordinary conditions, visual perception of distal objects (cars, tree, tables, books, etc.) remains quite accurate and stable, despite large variations in the proximal stimulus -- the pattern of light rays reaching the eyes. Every time you move or every time what you are looking at moves, the image it forms on the retina changes. Yet the object remains the same object. When saying the same word, different speakers produce different sound patterns, yet listeners hear the same word.
Two kinds of processes operate to achieve perceptual stability in the face of stimulus variation. One is familiarity or expectancy, based on experience. The other is "higher-order" stability, which perceptual systems automatically extract from the varying patterns of stimulation. I describe the higher-order stabilities first.
"Higher-order" refers to relations between parts of a stimulus array. "Higher-order stability" refers to the idea that some relations between parts of a complex stimulus remain unchanged or change predictably as the stimulus array changes.
The simplest example to understand is brightness constancy (more accurately, lightness constancy). A white piece of paper indoors reflects considerably less light than does a black lump of coal outside on a bright, sunny day. Yet the paper looks white, and the coal black.
Brightness constancy depends on extracting the per cent of light (albedo) that the coal and the paper reflect. This can be done by comparing the amount of light from the coal and from the paper to the average amount of light light from their surroundings. The paper reflects more light than its surrounding; the coal reflects less. So, even though the total amount of light from white paper (or balck coal) can vary greatly, the relation of light from white paper (or black coal) to light from the surroundings remains (relatively) unchanged -- a higher order stability. So the visual system compares light from each object to the light from its neighbors. This comparison gives an accurate estimate of the per cent of light that each object reflects.
As the distance of the object you look at the size of the image it makes on your retina varies, as Figure 1 illustrates.
The blue arrow and the red arrow are the same height, but the red arrow is twice as far away from the eye. So the image of the red arrow on the back of the eye (retina) is 1/2 as large. The green arrow is 1/2 the size of the blue and red arrows, and it is located at the same distance from the eye as is the blue arrow. So it makes an image that is 1/2 the blue arrow's image, but the same size as the red arrow's image.
If an observer cannot tell the distance of the arrows,
If adequate depth information is available in the visual stimulus, then perception of size becomes accurate. The visual system combines information from image size and image distance to achieve perceptual size constancy.
Figure 2 shows the effect of depth cues on the perception of size. Most observers perceive the four blue cylinders as about the same size, even though the size of the images gets progressively smaller from left to right. The linear perspective and texture gradient in the diagram provide strong depth cues. The visual perceptual system combines the distance and image size cues to produce the perception of (approximately) constant cylinder size.Brightness constancy and size constancy depend on a constant ratio between the object and some aspect of its surroundings: For brightness constancy the ratio of light reflected from the object and its surroundings remains constant. For size constancy, the ratio of image size and perceived distance remains constant. Other constancies depend on predictable changes in the relation between parts of the visual world.
For example, shape constancy depends on the predictable changes in the relations among an object's features as it moves in space. Consider a cube that rotates from its left to its right. An edge of the cube appears on the left side, gets larger, and moves faster and faster toward the middle. When it reaches the middle, the changes go in the exact reverse, until the edge disappears at the right. This transformation can be derived from a sine wave (basic trigonometric function generated by the rotation of a circle). The perceptual system appears to extract this stable pattern of change and uses it to represent the stability or constancy of the cube.
The same kind of predictable transformation underlies other kinds of constancies. As you walk or drive, the texture of the visual world expands predictably toward you from the point toward which you are moving. For example, as you walk down a hall as illustrated in Figure 3 below, the end of the hall casts a bigger and bigger image on the retina of your eye.
But the ratio of width to height for the hall (Width divided by height) remains unchanged (blue lines and numbers on the figure at the right). In addition, the change in the hall's width and height is completely determined. The surface texture of the walls, ceiling, and floor expands around you, as the red arrows in the figure at the right illustrate. The visual perceptual system uses these stable or predictable "higher-order" features to adjust for the changes in the stimulus array on the retina and maintain perceptual constancy.
This predictable transformation is the basis of motion parallax, the very strong and reliable monocular depth cue, described in the exercise on depth perception. As a sound source moves from your left to your right the time and intensity difference of the sound reaching your ear changes predictably. The visual and auditory perceptual systems appear to extract these predictable changes to create perceptual constancies.