Visual perceptionVisual perception is the ability to interpret the surrounding environment through photopic vision (daytime vision), color vision, scotopic vision (night vision), and mesopic vision (twilight vision), using light in the visible spectrum reflected by objects in the environment. This is different from visual acuity, which refers to how clearly a person sees (for example "20/20 vision"). A person can have problems with visual perceptual processing even if they have 20/20 vision.
PerceptionPerception () is the organization, identification, and interpretation of sensory information in order to represent and understand the presented information or environment. All perception involves signals that go through the nervous system, which in turn result from physical or chemical stimulation of the sensory system. Vision involves light striking the retina of the eye; smell is mediated by odor molecules; and hearing involves pressure waves.
Sensory cueA sensory cue is a statistic or signal that can be extracted from the sensory input by a perceiver, that indicates the state of some property of the world that the perceiver is interested in perceiving. A cue is some organization of the data present in the signal which allows for meaningful extrapolation. For example, sensory cues include visual cues, auditory cues, haptic cues, olfactory cues and environmental cues. Sensory cues are a fundamental part of theories of perception, especially theories of appearance (how things look).
Dynamic Bayesian networkA Dynamic Bayesian Network (DBN) is a Bayesian network (BN) which relates variables to each other over adjacent time steps. A Dynamic Bayesian Network (DBN) is often called a Two-Timeslice BN (2TBN) because it says that at any point in time T, the value of a variable can be calculated from the internal regressors and the immediate prior value (time T-1). DBNs were developed by Paul Dagum in the early 1990s at Stanford University's Section on Medical Informatics.
Bayesian networkA Bayesian network (also known as a Bayes network, Bayes net, belief network, or decision network) is a probabilistic graphical model that represents a set of variables and their conditional dependencies via a directed acyclic graph (DAG). It is one of several forms of causal notation. Bayesian networks are ideal for taking an event that occurred and predicting the likelihood that any one of several possible known causes was the contributing factor. For example, a Bayesian network could represent the probabilistic relationships between diseases and symptoms.
Visual captureIn psychology, visual capture is the dominance of vision over other sense modalities in creating a percept. In this process, the visual senses influence the other parts of the somatosensory system, to result in a perceived environment that is not congruent with the actual stimuli. Through this phenomenon, the visual system is able to disregard what other information a different sensory system is conveying, and provide a logical explanation for whatever output the environment provides.
Visual systemThe visual system comprises the sensory organ (the eye) and parts of the central nervous system (the retina containing photoreceptor cells, the optic nerve, the optic tract and the visual cortex) which gives organisms the sense of sight (the ability to detect and process visible light) as well as enabling the formation of several non-image photo response functions. It detects and interprets information from the optical spectrum perceptible to that species to "build a representation" of the surrounding environment.
McGurk effectThe McGurk effect is a perceptual phenomenon that demonstrates an interaction between hearing and vision in speech perception. The illusion occurs when the auditory component of one sound is paired with the visual component of another sound, leading to the perception of a third sound. The visual information a person gets from seeing a person speak changes the way they hear the sound. If a person is getting poor-quality auditory information but good-quality visual information, they may be more likely to experience the McGurk effect.
Bayesian probabilityBayesian probability (ˈbeɪziən or ˈbeɪʒən ) is an interpretation of the concept of probability, in which, instead of frequency or propensity of some phenomenon, probability is interpreted as reasonable expectation representing a state of knowledge or as quantification of a personal belief. The Bayesian interpretation of probability can be seen as an extension of propositional logic that enables reasoning with hypotheses; that is, with propositions whose truth or falsity is unknown.
Visual cultureVisual culture is the aspect of culture expressed in . Many academic fields study this subject, including cultural studies, art history, critical theory, philosophy, media studies, Deaf Studies, and anthropology. The field of visual culture studies in the United States corresponds or parallels the Bildwissenschaft ("image studies") in Germany. Both fields are not entirely new, as they can be considered reformulations of issues of photography and film theory that had been raised from the 1920s and 1930s by authors like Béla Balázs, László Moholy-Nagy, Siegfried Kracauer and Walter Benjamin.
