UPMC at MediaEval 2013: Relevance by Text and Diversity by Visual Clustering - Sorbonne Université Access content directly
Conference Papers Year : 2013

UPMC at MediaEval 2013: Relevance by Text and Diversity by Visual Clustering

Abstract

In the diversity task, our strategy was to, first, try to improve relevance, and then to cluster similar images to improve diversity. We propose a four step framework, based on AHC clustering and different reranking strategies. A large number of tests on devset showed that most of the best strategies include text based reranking for pertinence, and visual clustering for diversity - even compared to location based descriptors. Results on expert and crowd-sourcing testset grounds truths seem to confirm these observations.
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Dates and versions

hal-00925153 , version 1 (07-01-2014)

Identifiers

  • HAL Id : hal-00925153 , version 1

Cite

Christian Antonio Kuoman Mamani, Sabrina Tollari, Marcin Detyniecki. UPMC at MediaEval 2013: Relevance by Text and Diversity by Visual Clustering. MediaEval 2013 Multimedia Benchmark Workshop, Oct 2013, Barcelona, Spain. ⟨hal-00925153⟩
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