language: en

Consortium AVEIR at ImageCLEFphoto 2008: on the fusion of runs

Sabrina Tollari 1 , Marcin Detyniecki 1 , Marin Ferecatu 2 , Hervé Glotin 3 , Philippe Mulhem 4 , Massih-Reza Amini 1 , Ali Fakeri-Tabrizi 1 , Patrick Gallinari 1 , Hichem Sahbi 2 , Zhong-Qiu Zhao 3
1 Université Pierre et Marie Curie-Paris6, UMR CNRS 7606-LIP6,
Paris,
firstname.lastname@lip6.fr
2 TELECOM ParisTech, UMR CNRS 5141 LTCI,
Paris,
firstname.lastname@telecom-paristech.fr
3 Université du Sud Toulon-Var, UMR CNRS 6168 LSIS,
Toulon,
name@univ-tln.fr
4 Université Joseph Fourier, UMR CNRS 5217 LIG,
Grenoble,
firstname.lastname@imag.fr

Abstract In this working note, we present the submission of the AVEIR consortium, composed of 4 French laboratories, to ImageCLEFphoto 2008. The submitted runs correspond to different fusion strategies applied to four individual ranks, each proposed by an AVEIR consortium partner. In particular, we study the complete, and partial, average of the ranking values, the minimum of these values, and a random based diversification. We first briefly describe the individual run of each partner, then we describe the fusion runs. The official results classed one of the runs, the MEAN fusion, as the third best in the automatic text-image run category. This run gives better results than the best partner run.

Categories and Subject Descriptors H.3 [Information Storage and Retrieval]: H.3.1 Content Analysis and Indexing; H.3.3 Information Search and Retrieval; H.3.4 Systems and Software; H.3.7 Digital Libraries; H.2.3 [Database Management]: Languages?Query Languages General Terms Measurement, Performance, Experimentation Keywords Rank Fusion, Image Retrieval, Multimodal Information Retrieval

1 Introduction