Visual perception
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Visual perception is the ability to interpret the surrounding
The resulting perception is also known as vision, sight, or eyesight (adjectives visual, optical, and ocular, respectively). The various physiological components involved in vision are referred to collectively as the visual system, and are the focus of much research in linguistics, psychology, cognitive science, neuroscience, and molecular biology, collectively referred to as vision science.
Visual system
In humans and a number of other mammals, light enters the eye through the
The lateral geniculate nucleus sends signals to
The human visual system is generally believed to be sensitive to
Study
The major problem in visual perception is that what people see is not simply a translation of retinal stimuli (i.e., the image on the retina), with the brain altering the basic information taken in. Thus people interested in perception have long struggled to explain what visual processing does to create what is actually seen.
Early studies
There were two major ancient Greek schools, providing a primitive explanation of how vision works.
The first was the "emission theory" of vision which maintained that vision occurs when rays emanate from the eyes and are intercepted by visual objects. If an object was seen directly it was by 'means of rays' coming out of the eyes and again falling on the object. A refracted image was, however, seen by 'means of rays' as well, which came out of the eyes, traversed through the air, and after refraction, fell on the visible object which was sighted as the result of the movement of the rays from the eye. This theory was championed by scholars who were followers of Euclid's Optics and Ptolemy's Optics.
The second school advocated the so-called 'intromission' approach which sees vision as coming from something entering the eyes representative of the object. With its main propagator Aristotle (De Sensu),[7] and his followers,[7] this theory seems to have some contact with modern theories of what vision really is, but it remained only a speculation lacking any experimental foundation. (In eighteenth-century England, Isaac Newton, John Locke, and others, carried the intromission theory of vision forward by insisting that vision involved a process in which rays—composed of actual corporeal matter—emanated from seen objects and entered the seer's mind/sensorium through the eye's aperture.)[8]
Both schools of thought relied upon the principle that "like is only known by like", and thus upon the notion that the eye was composed of some "internal fire" that interacted with the "external fire" of visible light and made vision possible.
Leonardo da Vinci (1452–1519) is believed to be the first to recognize the special optical qualities of the eye. He wrote "The function of the human eye ... was described by a large number of authors in a certain way. But I found it to be completely different." His main experimental finding was that there is only a distinct and clear vision at the line of sight—the optical line that ends at the fovea. Although he did not use these words literally he actually is the father of the modern distinction between foveal and peripheral vision.[12]
Isaac Newton (1642–1726/27) was the first to discover through experimentation, by isolating individual colors of the spectrum of light passing through a prism, that the visually perceived color of objects appeared due to the character of light the objects reflected, and that these divided colors could not be changed into any other color, which was contrary to scientific expectation of the day.[3]
Unconscious inference
Inference requires prior experience of the world.
Examples of well-known assumptions, based on visual experience, are:
- light comes from above;
- objects are normally not viewed from below;
- faces are seen (and recognized) upright;[14]
- closer objects can block the view of more distant objects, but not vice versa; and
- figures (i.e., foreground objects) tend to have convex borders.
The study of
Another type of unconscious inference hypothesis (based on probabilities) has recently been revived in so-called
Gestalt theory
Gestalt psychologists working primarily in the 1930s and 1940s raised many of the research questions that are studied by vision scientists today.[18]
The Gestalt Laws of Organization have guided the study of how people perceive visual components as organized patterns or wholes, instead of many different parts. "Gestalt" is a German word that partially translates to "configuration or pattern" along with "whole or emergent structure". According to this theory, there are eight main factors that determine how the visual system automatically groups elements into patterns: Proximity, Similarity, Closure, Symmetry, Common Fate (i.e. common motion), Continuity as well as Good Gestalt (pattern that is regular, simple, and orderly) and Past Experience.[citation needed]
Analysis of eye movement
During the 1960s, technical development permitted the continuous registration of eye movement during reading,[19] in picture viewing,[20] and later, in visual problem solving,[21] and when headset-cameras became available, also during driving.[22]
The picture to the right shows what may happen during the first two seconds of visual inspection. While the background is out of focus, representing the peripheral vision, the first eye movement goes to the boots of the man (just because they are very near the starting fixation and have a reasonable contrast). Eye movements serve the function of attentional selection, i.e., to select a fraction of all visual inputs for deeper processing by the brain.[citation needed]
The following fixations jump from face to face. They might even permit comparisons between faces.[citation needed]
It may be concluded that the icon face is a very attractive search icon within the peripheral field of vision. The
It can also be noted that there are different types of eye movements:
Face and object recognition
There is considerable evidence that face and
The inferotemporal cortex has a key role in the task of recognition and differentiation of different objects. A study by MIT shows that subset regions of the IT cortex are in charge of different objects.[29] By selectively shutting off neural activity of many small areas of the cortex, the animal gets alternately unable to distinguish between certain particular pairments of objects. This shows that the IT cortex is divided into regions that respond to different and particular visual features. In a similar way, certain particular patches and regions of the cortex are more involved in face recognition than other object recognition.
Some studies tend to show that rather than the uniform global image, some particular features and regions of interest of the objects are key elements when the brain needs to recognise an object in an image.[30][31] In this way, the human vision is vulnerable to small particular changes to the image, such as disrupting the edges of the object, modifying texture or any small change in a crucial region of the image.[32]
Studies of people whose sight has been restored after a long blindness reveal that they cannot necessarily recognize objects and faces (as opposed to color, motion, and simple geometric shapes). Some hypothesize that being blind during childhood prevents some part of the visual system necessary for these higher-level tasks from developing properly.[33] The general belief that a critical period lasts until age 5 or 6 was challenged by a 2007 study that found that older patients could improve these abilities with years of exposure.[34]
Cognitive and computational approaches
In the 1970s, David Marr developed a multi-level theory of vision, which analyzed the process of vision at different levels of abstraction. In order to focus on the understanding of specific problems in vision, he identified three levels of analysis: the computational, algorithmic and implementational levels. Many vision scientists, including Tomaso Poggio, have embraced these levels of analysis and employed them to further characterize vision from a computational perspective.[35]
The computational level addresses, at a high level of abstraction, the problems that the visual system must overcome. The algorithmic level attempts to identify the strategy that may be used to solve these problems. Finally, the implementational level attempts to explain how solutions to these problems are realized in neural circuitry.
Marr suggested that it is possible to investigate vision at any of these levels independently. Marr described vision as proceeding from a
- A 2D or primal sketch of the scene, based on feature extraction of fundamental components of the scene, including edges, regions, etc. Note the similarity in concept to a pencil sketch drawn quickly by an artist as an impression.
- A 21⁄2 D sketch of the scene, where textures are acknowledged, etc. Note the similarity in concept to the stage in drawing where an artist highlights or shades areas of a scene, to provide depth.
- A 3 D model, where the scene is visualized in a continuous, 3-dimensional map.[36]
Marr's 21⁄2D sketch assumes that a depth map is constructed, and that this map is the basis of
A more recent, alternative framework proposes that vision is composed instead of the following three stages: encoding, selection, and decoding.[40] Encoding is to sample and represent visual inputs (e.g., to represent visual inputs as neural activities in the retina). Selection, or attentional selection, is to select a tiny fraction of input information for further processing, e.g., by shifting gaze to an object or visual location to better process the visual signals at that location. Decoding is to infer or recognize the selected input signals, e.g., to recognize the object at the center of gaze as somebody's face. In this framework,[41] attentional selection starts at the primary visual cortex along the visual pathway, and the attentional constraints impose a dichotomy between the central and peripheral visual fields for visual recognition or decoding.
Transduction
Transduction is the process through which energy from environmental stimuli is converted to neural activity. The
Opponent process
Transduction involves chemical messages sent from the photoreceptors to the bipolar cells to the ganglion cells. Several photoreceptors may send their information to one ganglion cell. There are two types of ganglion cells: red/green and yellow/blue. These neurons constantly fire—even when not stimulated. The brain interprets different colors (and with a lot of information, an image) when the rate of firing of these neurons alters. Red light stimulates the red cone, which in turn stimulates the red/green ganglion cell. Likewise, green light stimulates the green cone, which stimulates the green/red ganglion cell and blue light stimulates the blue cone which stimulates the blue/yellow ganglion cell. The rate of firing of the ganglion cells is increased when it is signaled by one cone and decreased (inhibited) when it is signaled by the other cone. The first color in the name of the ganglion cell is the color that excites it and the second is the color that inhibits it. i.e.: A red cone would excite the red/green ganglion cell and the green cone would inhibit the red/green ganglion cell. This is an opponent process. If the rate of firing of a red/green ganglion cell is increased, the brain would know that the light was red, if the rate was decreased, the brain would know that the color of the light was green.[44]
Artificial visual perception
Theories and observations of visual perception have been the main source of inspiration for computer vision (also called machine vision, or computational vision). Special hardware structures and software algorithms provide machines with the capability to interpret the images coming from a camera or a sensor.
For instance, the 2022
See also
- Color vision
- Computer vision
- Depth perception
- Entoptic phenomenon
- Gestalt psychology
- Lateral masking
- Looming
- Naked eye
- Machine vision
- McGill Picture Anomaly Test
- Motion perception
- Multisensory integration
- Interpretation (philosophy)
- Spatial frequency
- Visual illusion
- Visual processing
- Visual system
- Sensations
Vision deficiencies or disorders
Related disciplines
References
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- ^ Yarbus, A. L. (1967). Eye movements and vision, Plenum Press, New York[page needed]
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Further reading
- Von Helmholtz, Hermann (1867). Handbuch der physiologischen Optik. Vol. 3. Leipzig: Voss. Quotations are from the English translation produced by the Optical Society of America (1924–25): Treatise on Physiological Optics Archived September 27, 2018, at the Wayback Machine.
External links
- The Organization of the Retina and Visual System
- Effect of Detail on Visual Perception by Jon McLoone, the Wolfram Demonstrations Project
- The Joy of Visual Perception, resource on the eye's perception abilities.
- VisionScience. Resource for Research in Human and Animal Vision A collection of resources in vision science and perception
- Vision and Psychophysics
- Vision, Scholarpedia Expert articles about Vision
- What are the limits of human vision?