Semantic Retrieval of Multimedia by Concept Languages

[Treating semantic concepts like words] Despite the quantum leap in computing performance, semantic retrieval of multimedia remains an unsolved problem. At the heart of the challenge is managing semantics. A retrieval engine works to bring together a set of documents that are relevant to a query. However, humans are endowed with such sophisticated relational competence that we effortlessly relate a concept to a great many others. For example, when we search for rose, we may relate it with a prickly fragrant flower, a person named Rose, or equally, a rock band called Guns N ’ Roses. Consequently, retrieving multimedia requires a means by which semantics can be specified and a mechanism through which relevant documents can be brought together. In this article, we describe a retrieval approach based on concept languages. We show how the latter can be used as a compelling means to express semantics and demonstrate how it can serve as an efficient mechanism to collocate documents. 1053-5888/06/$20.00©2006IEEE IEEE SIGNAL PROCESSING MAGAZINE [115] MARCH 2006EARLIER WORKS In content-based retrieval (CBR), the main approach has so far centered on the use of perceptual features—i.e., audio and visual descriptors extracted from a document [1], [2]. At first

Retrieval for color artistry concepts

Abstract—This paper presents a work on the retrieval of artworks for color artistry concepts. First we affirm the view that the Query-by-Example paradigm fundamental to the current content-based retrieval systems is able to extend only limited usefulness. We then propose a concept-based retrieval engine based on the generative grammar of elemental concepts methodology. In the latter, the language by which color artistry concepts are communicated in artworks is used to operate semantic searches. The color artistry language is explicated into elemental concepts and the associated generative grammar. The elemental concepts are used to index the artworks, while the generative grammar is used to facilitate post-coordinate expression of color artistry concept queries by using the elemental concepts. Index Terms—Color artistry concepts, concept-based retrieval, generative grammar of elecepts. I