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Placing images with refined language models and similarity search with PCA-reduced VGG features

G. Kordopatis-Zilos 1 A. Popescu 2 S. Papadopoulos 1 Y. Kompatsiaris 1
1 CERTH ITI - CERTH Information Technologies Institute
2 DIASI - Département Intelligence Ambiante et Systèmes Interactifs
Abstract : We describe the participation of the CERTH/CEA-LIST team in the MediaEval 2016 Placing Task. We submitted five runs to the estimation-based sub-task: one based only on text by employing a Language Model-based approach with several refinements, one based on visual content, using geospatial clustering over the most visually similar images, and three based on a hybrid scheme exploiting both visual and textual cues from the multimedia items, trained on datasets of different size and origin. The best results were obtained by a hybrid approach trained with external training data and using two publicly available gazetteers.
Keywords : Similarity search Visual content Visual languages Multimedia items Language model Hybrid scheme Hybrid approach Geospatial clustering Different sizes Computational linguistics
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Conference papers
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https://hal-cea.archives-ouvertes.fr/cea-01843183
Contributor : Léna Le Roy <>
Submitted on : Wednesday, July 18, 2018 - 3:55:57 PM
Last modification on : Monday, February 10, 2020 - 6:13:48 PM

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G. Kordopatis-Zilos, A. Popescu, S. Papadopoulos, Y. Kompatsiaris. Placing images with refined language models and similarity search with PCA-reduced VGG features. 2016 Multimedia Benchmark Workshop, MediaEval 2016, Oct 2016, Hilversum, Netherlands. ⟨cea-01843183⟩

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