Using Visual Concept Features in a Multimodal Retrieval System for the Medical Collection at ImageCLEF2012.
Ángel Castellanos, Joan Benavent, Xaro Benavent, Ana M. García-Serrano, Esther de Ves · 2012
Abstract. The main goal of this paper is to present our experiments in the classification modality and in the ad-hoc image retrieval tasks with the Medical collection at ImageCLEF 2012 Campaign. This edition we focus on applying new strategies for both the textual and the visual subsystems included in our multimodal retrieval system. The visual subsystem has focus on extending the low-level features vector with concept features. These concept features have been calculated by means of a logistic regression model. The textual subsystem has focus on applying a query reformulation to remove general and domain stop-words, trying to produce a query with only medical-related terms. We have not obtained the results as good as obtained at the Photo annotation retrieval subtask using similar techniques. Therefore, a deep analysis for the Medical collection will be done.