  The Visual Object Information Retrieval (VOIR) system described in this paper
implements an image retrieval approach that combines two layers, the conceptual
and the visual layer. It uses terms from a textual thesaurus to represent the
conceptual information and also works with image regions, the visual
information. The terms are related with the image regions through a weighted
association enabling the execution of concept-level queries. VOIR uses
region-based relevance feedback to improve the quality of the results in each
query session and to discover new associations between text and image. This
paper describes a user-centred and task-oriented comparative evaluation of VOIR
which was undertaken considering three distinct versions of VOIR: a full-fledge
version; one supporting relevance feedback only at image level; and a third
version not supporting relevance feedback at all. The evaluation performed
showed the usefulness of region based relevance feedback in the context of VOIR
prototype.
