On the burstiness of visual elements

Hervé Jégou 1, 2 Matthijs Douze 1 Cordelia Schmid 1
1 LEAR - Learning and recognition in vision
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
2 TEXMEX - Multimedia content-based indexing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : Burstiness, a phenomenon initially observed in text retrieval, is the property that a given visual element appears more times in an image than a statistically independent model would predict. In the context of image search, burstiness corrupts the visual similarity measure, i.e., the scores used to rank the images. In this paper, we propose a strategy to handle visual bursts for bag-of-features based image search systems. Experimental results on three reference datasets show that our method significantly and consistently outperforms the state of the art.
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https://hal.inria.fr/inria-00394211
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Submitted on : Tuesday, June 7, 2011 - 10:24:50 AM
Last modification on : Monday, December 17, 2018 - 11:22:02 AM
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Hervé Jégou, Matthijs Douze, Cordelia Schmid. On the burstiness of visual elements. CVPR 2009 - IEEE Conference on Computer Vision and Pattern Recognition, Jun 2009, Miami, United States. pp.1169-1176, ⟨10.1109/CVPRW.2009.5206609⟩. ⟨inria-00394211v3⟩

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