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Communication Dans Un Congrès Année : 2014

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

Résumé

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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Dates et versions

hal-00995334 , version 1 (23-05-2014)

Identifiants

  • HAL Id : hal-00995334 , version 1

Citer

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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