Query-by-example video retrieval is receiving an increasing attention in recent years. One of the state-of-art approaches is the Bag-of-visual Words (BoW) based technique, where images are described by a set of local features mapped to a discrete set of visual words. Such techniques, however, ignores spatial relations between visual words. In this paper, we present a content based video retriev...

Dimensionality reduction in the bag-of-words vector space document representation model has been widely studied for the purposes of improving accuracy and reducing computational load of document retrieval tasks. These techniques, however, have not been studied to the same degree with regard to document clustering tasks. This study evaluates the effectiveness of two popular dimensionality reduct...

In this paper we present the first Content-Based Image Retrieval (CBIR) framework in the field of in vivo endomicroscopy, with applications ranging from training support to diagnosis support. We propose to adjust the standard Bag-of-Visual-Words method for the retrieval of endomicroscopic videos. Retrieval performance is evaluated both indirectly from a classification point-of-view, and directl...

In this paper, we present an adaptation the Bag of Features (BoF) concept to 3D shape retrieval problems. The BoF approach has recently become one of the most popular methods in 2D image retrieval. We extent this approach from 2D images to 3D shapes. Following the BoF outline, we address the necessary modifications for the 3D extension and present novel solutions for the parameterization of 3D ...

This paper investigates the capabilities of the Bag-of-Words (BWs) method in the 3D shape retrieval field. The contributions of this paper are (1) the 3D shape retrieval task is categorized from different points of view: specific versus generic, partial-toglobal retrieval (PGR) versus global-to-global retrieval (GGR), and articulated versus nonarticulated (2) the spatial information, represente...

We address the problem of large scale image retrieval in a wide-baseline setting, where for any query image all the matching database images will come from very different viewpoints. In such settings traditional bag-of-visual-words approaches are not equipped to handle the significant feature descriptor transformations that occur under large camera motions. In this paper we present a novel appr...

(Chapter in Springer book ”Current Challenges in Patent Information Retrieval”, to appear in May 2011) This paper takes a fresh look at an old idea in Information Retrieval: the use of linguistically extracted phrases as terms in the automatic categorization of documents, and in particular the pre-classification of patent applications. In Information Retrieval, until now there was found little ...