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Communication dans un congrès

Spatio-Temporal Saliency Detection in Dynamic Scenes using Local Binary Patterns

Abstract : Visual saliency detection is an important step in many computer vision applications, since it reduces further processing steps to regions of interest. Saliency detection in still images is a well-studied topic. However, videos scenes contain more information than static images, and this additional temporal information is an important aspect of human perception. Therefore, it is necessary to include motion information in order to obtain spatio-temporal saliency map for a dynamic scene. In this paper, we introduce a new spatio-temporal saliency detection method for dynamic scenes based on dynamic textures computed with local binary patterns. In particular, we extract local binary patterns descriptors in two orthogonal planes (LBP-TOP) to describe temporal information, and color features are used to represent spatial information. The obtained three maps are finally fused into a spatio-temporal saliency map. The algorithm is evaluated on a dataset with complex dynamic scenes and the results show that our proposed method outperforms state-of-art methods.
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Communication dans un congrès
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Contributeur : Désiré Sidibé Connectez-vous pour contacter le contributeur
Soumis le : vendredi 23 mai 2014 - 10:28:00
Dernière modification le : dimanche 26 juin 2022 - 00:43:46
Archivage à long terme le : : samedi 23 août 2014 - 11:25:21


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  • HAL Id : hal-00995334, version 1


Satya Muddamsetty, Désiré Sidibé, Alain Trémeau, Fabrice Meriaudeau. Spatio-Temporal Saliency Detection in Dynamic Scenes using Local Binary Patterns. ICPR, Aug 2014, Stockholm, Sweden. pp.1-6. ⟨hal-00995334⟩



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