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• W2005347316 abstract "Local image features are often used to efficiently represent image content. The limited number of types of features that a local feature extractor responds to might be insufficient to provide a robust image representation. To overcome this limitation, we propose a context-aware feature extraction formulated under an information theoretic framework. The algorithm does not respond to a specific type of features; the idea is to retrieve complementary features which are relevant within the image context. We empirically validate the method by investigating the repeatability, the completeness, and the complementarity of context-aware features on standard benchmarks. In a comparison with strictly local features, we show that our context-aware features produce more robust image representations. Furthermore, we study the complementarity between strictly local features and context-aware ones to produce an even more robust representation." @default.
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• W2005347316 date "2014-02-01" @default.
• W2005347316 modified "2023-09-24" @default.
• W2005347316 title "Context-aware features and robust image representations" @default.
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• W2005347316 doi "https://doi.org/10.1016/j.jvcir.2013.10.006" @default.
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