Media analysis algorithms are used for a variety of purposes. They may improve media facets such as contrast or signal-to-noise ratio or extract lowlevel details such asMPEG-7 features to be used in data mining and other higherlevel processing. However, algorithms are difficult to manage, understand and apply in particular for non-expert users. Therefore we are developing an algorithm ontology to support identification, aggregation and recording of algorithms for media analysis. This is especially useful for domains with high-volumes of complex media objects to investigate and integrate. Algorithms for media analysis may be applied at multiple points within a typical multimedia lifecycle. This article discusses a proposed algorithm ontology to support identification, retrieval and application of multimedia analysis processes and its application to metadata management and multimedia interoperability.
Media Analysis and the Algorithm Ontology
Asirelli P;Colantonio S;Martinelli M;Salvetti O
2008
Abstract
Media analysis algorithms are used for a variety of purposes. They may improve media facets such as contrast or signal-to-noise ratio or extract lowlevel details such asMPEG-7 features to be used in data mining and other higherlevel processing. However, algorithms are difficult to manage, understand and apply in particular for non-expert users. Therefore we are developing an algorithm ontology to support identification, aggregation and recording of algorithms for media analysis. This is especially useful for domains with high-volumes of complex media objects to investigate and integrate. Algorithms for media analysis may be applied at multiple points within a typical multimedia lifecycle. This article discusses a proposed algorithm ontology to support identification, retrieval and application of multimedia analysis processes and its application to metadata management and multimedia interoperability.File | Dimensione | Formato | |
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