Automatic multimedia annotation through kernel combinations

Abstract

An image classification model is here presented based on the integration of visual and textual properties supported by complex kernel functions. Linguistic descriptions derived through Information Extraction from Web pages are here integrated with the visual features corresponding to the images, according to independent kernel combinations. The impact of dimensionality reduction methods (i.e. LSA) and of proper combinations of redundant feature descriptions is also presented. The resulting workflow is largely applicable as the comparative evaluation discussed here confirms.