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Concept
Structural information theory
Summary
Structural information theory (SIT) is a theory about human perception and in particular about visual perceptual organization, which is a neuro-cognitive process. It has been applied to a wide range of research topics, mostly in visual form perception but also in, for instance, visual ergonomics, data visualization, and music perception.
SIT began as a quantitative model of visual pattern classification. Nowadays, it includes quantitative models of symmetry perception and amodal completion, and is theoretically sustained by a perceptually adequate formalization of visual regularity, a quantitative account of viewpoint dependencies, and a powerful form of neurocomputation. SIT has been argued to be the best defined and most successful extension of Gestalt ideas. It is the only Gestalt approach providing a formal calculus that generates plausible perceptual interpretations.
A simplest code is a code with minimum information load, that is, a code that enables a reconstruction of the stimulus using a minimum number of descriptive parameters. Such a code is obtained by capturing a maximum amount of visual regularity and yields a hierarchical organization of the stimulus in terms of wholes and parts.
The assumption that the visual system prefers simplest interpretations is called the simplicity principle. Historically, the simplicity principle is an information-theoretical translation of the Gestalt law of Prägnanz, which was inspired by the natural tendency of physical systems to settle into relatively stable states defined by a minimum of free-energy. Furthermore, just as the later-proposed minimum description length principle in algorithmic information theory (AIT), a.k.a. the theory of Kolmogorov complexity, it can be seen as a formalization of Occam's Razor, according to which the simplest interpretation of data is the best one.
Crucial to the latter finding is the distinction between, and integration of, viewpoint-independent and viewpoint-dependent factors in vision, as proposed in SIT's empirically successful model of amodal completion.
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