Multimedia Retrieval in a Medical Image Collection: Results Using Modality Classes
The effective communication between user and systems is one main aim in the Multimedia Information Retrieval field. In this paper the modality classification of images is used to expand the user queries within the ImageCLEF Medical Retrieval collection provided by organizers. Our main contribution is to show how and when results can be improved by understanding modality-related challenges. To do so, a detailed analysis of the results of the experiments carried out is presented and the comparison between these results shows that the improvement using modality class query expansion is query-dependent.
FCA-based knowledge representation and local generalized linear models to address relevance and diversity in diverse social images
Abstract In social image retrieval, the main goal is to offer a relevant but also diverse result set of images to the user. To address relevance and diversity at the same time, we propose a multi-modal procedure. This approach deals with the diversification problem using a two-step procedure based on the application of Formal Concept Analysis (FCA) to organize the text content of the images, followed by a Hierarchical Agglomerative Clustering (HAC) step to find the topics addressed by the images. FCA detects the latent concepts covered by the images in the result set, organizing them according to these concepts. In the second step, clustering is carried out to group together the ones with a…
Multimedia Retrieval by Means of Merge of Results from Textual and Content Based Retrieval Subsystems
The main goal of this paper it is to present our experiments in ImageCLEF 2009 Campaign (photo retrieval task). In 2008 we proved empirically that the Text-based Image Retrieval (TBIR) methods defeats the Content-based Image Retrieval CBIR "quality" of results, so this time we developed several experiments in which the CBIR helps the TBIR. The TBIR System [6] main improvement is the named-entity sub-module. In case of the CBIR system [3] the number of low-level features has been increased from the 68 component used at ImageCLEF 2008 up to 114 components, and only the Mahalanobis distance has been used. We propose an ad-hoc management of the topics delivered, and the generation of XML struct…
Some Results Using Different Approaches to Merge Visual and Text-Based Features in CLEF’08 Photo Collection
This paper describes the participation of the MIRACLE team at the ImageCLEF Photographic Retrieval task of CLEF 2008. We succeeded in submitting 41 runs. Obtained results from text-based retrieval are better than content-based as previous experiments in the MIRACLE team campaigns [5, 6] using different software. Our main aim was to experiment with several merging approaches to fuse text-based retrieval and content-based retrieval results, and it happened that we improve the text-based baseline when applying one of the three merging algorithms, although visual results are lower than textual ones.