REGIMvid at ImageCLEF2012: Concept-based Query Refinement and Relevance-based Ranking Enhancement for Image Retrieval

In this paper, we present our proposed approach that deals with two important steps in the retrieval process, which are query analysis and relevance-based ranking. First, query analysis takes into account two forms of queries: textual and visual which present the form of queries provided by ImageCLEF in the task “Visual concept detection, annotation, and retrieval using Flickr photos ”. The main idea in the query analysis process is to interpret the textual and visual queries and select the most appropriate concepts according to the query to concept mapping. Even the list of concepts is retained, we perform a query refinement process to improve the quality of the interpretation of the query. Second, we try to achieve a high-quality relevance-based result not only with choosing an adequate similarity measure but also with enhancing obtained scores by elaborating a random walk with restart, which is performed over inter-images semantic similarity graph.