The learning-enhanced relevance feedback has been one of the most active research areas in content-based image retrieval in recent years. However, few methods using the relevance ...
In this paper we present a complete method to retrieve reliable correspondences among wide baseline images, that is images of the same scene/object acquired from very different vi...
Francesco Colletto, Marco Marcon, Augusto Sarti, S...
In this paper we offer several new insights and techniques for effectively using color and texture to simultaneously convey information about multiple 2D scalar and vector distrib...
Timothy Urness, Victoria Interrante, Ivan Marusic,...
Learning the user’s semantics for CBIR involves two different sources of information: the similarity relations entailed by the content-based features, and the relevance relatio...
This paper presents a new statistical image segmentation algorithm, in which the texture features are modeled by Symmetric Alpha-Stable (SαS) distributions. These features are ef...