ARTEMIS @ MediaEval 2013: A Content - Based Image Clustering Method for Public Image Repositories

Andrei Bursuc (1, 2, 3) , Zaharia Titus (1, 2)

1 TSP - ARTEMIS - Département Advanced Research And Techniques For Multidimensional Imaging Systems
2 MAP5 - UMR 8145 - Mathématiques Appliquées Paris 5
3 CAOR - Centre de Robotique

In this paper, we describe our approach and its results as part of the MediaEval 2013 Retrieving Diverse Social Images Task evaluation. We illustrate a content - based technique relying on a single type of visual descriptors that makes it possible to identify groups of similar instances of a given landmark and select the most representative images from each such group out of a set of relatively noisy or redundant images. This method builds for each landmark a matching graph through quantized interest points similarities and identifies groups of similar instances of the landmark as connected components. In this approach we do not make use of the textual metadata of the images or any other external source of information.

Domaines: Multimédia [cs.MM]; Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Andrei Bursuc, Zaharia Titus. ARTEMIS @ MediaEval 2013: A Content - Based Image Clustering Method for Public Image Repositories. MediaEval 2013 Workshop, 2013, pp.1-2. ⟨hal-00944824⟩