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Analysis and interpretation of visual scenes through collaborative approaches

Abstract : During the last years, we have witnessed a great increase in the size of digital video collections. Efficient searching and browsing through such collections requires an indexing according to various meaningful terms, bringing us to the focus of this thesis, the automatic semantic indexing of videos. Within this topic, the Bag of Words (BoW) model, often employing SIFT or SURF features, has shown good performance especially on static images. As our first contribution, we propose to improve the results of SIFT/SURF BoW descriptors on videos by pre-processing the videos with a model of the human retina, thereby making these descriptors more robust to video degradations and sensitivite to spatio-temporal information. Our second contribution is a set of BoW descriptors based on trajectories. These give additional motion information, leading to a richer description of the video. Our third contribution, motivated by the availability of complementary descriptors, is a late fusion approach that automatically determines how to combine a large set of descriptors, giving a high increase in the average precision of detected concepts. All the proposed approaches are validated on the TRECVid challenge datasets which focus on visual concept detection in very large and uncontrolled multimedia content.
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Sabin Tiberius Strat. Analysis and interpretation of visual scenes through collaborative approaches. Other. Université de Grenoble; Universitatea politehnica (Bucarest), 2013. English. ⟨NNT : 2013GRENA026⟩. ⟨tel-00959081v3⟩

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