LAPI @ 2014 Retrieving Diverse Social Images Task: A Relevance Feedback Diversification Perspective

In this paper we approach the 2014 MediaEval Retrieving Diverse Social Images Task from the perspective of relevance feedback techniques. Two methods are introduced. A first approach exploits real user feedback with a multi Support Vector Machine classification scheme and a confidence score based image selection mechanism. The second approach replaces human feedback with an automatic hierarchical clustering pseudo-relevance feedback. The proposed relevance feedback approaches are designed to have in priority the diversification of the results, in contrast to most of the existing techniques that address only the relevance. Methods are tested on the benchmarking data and results are analyzed. Insights for future work conclude the paper.

[1]  Bogdan Ionescu,et al.  A relevance feedback perspective to image search result diversification , 2014, 2014 IEEE 10th International Conference on Intelligent Computer Communication and Processing (ICCP).

[2]  Bruno Emond,et al.  Multimedia and human-in-the-loop: interaction as content enrichment , 2007, HCM '07.

[3]  Jing Li,et al.  Relevance Feedback in Content-Based Image Retrieval: A Survey , 2013, Handbook on Neural Information Processing.