Searching through Photographic Databases with QuickLook

摘要

We present here the results obtained by including a new image descriptor, that we called prosemantic feature vector, within the framework of QuickLook image retrieval system. By coupling the prosemantic features and the relevance feedback mechanism provided by QuickLook, the user can move in a more rapid and precise way through the feature space toward the intended goal. The prosemantic features are obtained by a two-step feature extraction process. At the first step, low level features related to image structure and color distribution are extracted from the images. At the second step, these features are used as input to a bank of classifiers, each one trained to recognize a given semantic category, to produce score vectors. We evaluated the efficacy of the prosemantic features under search tasks on a dataset provided by Fratelli Alinari Photo Archive.