NDLI: A paradigm for semantic picture recognition

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A paradigm for semantic picture recognition

Content Provider	ACM Digital Library
Author	Baird, Michael L.
Abstract	Current syntactic (linguistic, grammarbased) approaches to picture recognition are found to have two basic limitations: (1) An inability to utilize contextual information to resolve ambiguities. For example, a “circle” may represent an eye, the sun, a ball, etc., and only through an analysis of the context (scene) in which the object is found can such ambiguities be resolved. (2) An inability to adequately describe a class of pictures in which non-pictorial paraphrase arises. That is, an inability to describe the possibly infinite variety of shapes of objects in a class, where each object is recognizable, completely out of context. Thus, while the human recognition of pictures is based on a combination of context analzsis and analysis of shape (internal structure), syntactic recognition is based only on an incomplete ability to analyze simple shapes. A paradigm for picture recognition has been developed and evaluated which overcomes some of the limitations of syntactic techniques. Because the paradigm permits the exhibition of properties and relations of a non-pictorial kind it is termed a semantic paradigm. Explicit use is made of contextual information in the form of “rules of inference”, and recognition is based on intensional class descriptions. Thus, cases of non-pictorial paraphrase, for which syntactic extensional descriptions are often inadequate, are now subject to analysis through the use of the semantic paradigm. Evaluation of the semantic paradigm has been based on its application to problems involving ambiguity of shape, non-pictorial paraphrase, non-ideal (tv scan) data, and multistability in perception.
File Format	PDF
DOI	10.1145/800192.805762
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	1973-08-27
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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