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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Saliency Detection Using Joint Temporal and Spatial Decorrelation
verfasst von : Hamed Rezazadegan Tavakoli, Esa Rahtu, Janne Heikkilä
Erschienen in: Image Analysis
Verlag: Springer Berlin Heidelberg
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This article presents a scene-driven (i.e. bottom-up) visual saliency detection technique for videos. The proposed method utilizes non-negative matrix factorization (NMF) to replicate neural responses of primary visual cortex neurons in spatial domain. In temporal domain, principal component analysis (PCA) was applied to imitate the effect of stimulus change experience during neural adaptation phenomena. We apply the proposed saliency model to background subtraction problem. The proposed method does not rely on any background model and is purely unsupervised. In experimental results, it will be shown that the proposed method competes well with some of the state-of-the-art background subtraction techniques especially in dynamic scenes.