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Local Saliency Estimation and Global Homogeneity Refinement for Video Saliency Detection

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Intelligent Interactive Multimedia Systems and Services (KES-IIMSS-18 2018)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 98))

Abstract

Saliency detection aims to segment the object of interest from the rest of the scene. While there has been a big number of saliency detection methods in still images, video saliency is in its early stages. In this paper, we propose a two stages video saliency detection method using local saliency estimation and global homogeneity refinement. Starting from a patch, the problem of saliency detection is modeled as a growing region which starts from a patch with high saliency information to the background. Local saliency is measured by combining spatial priors presented by local surrounding contrast with temporal information issued from the motion estimation feature. Temporal and spatial information are fused and then used to label each patch as foreground and background patches and produce the final saliency maps. Finally, Global homogeneity refinement is used to refine the saliency results by evaluating the foreground and background probabilities ratio propagated from the patches. Experiments have proved that the proposed method outperforms state-of-the-art methods over two benchmark datasets.

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Author information

Authors and Affiliations

  1. Networked Objects Control and Communication Systems Laboratory, Pôle technologique de Sousse, Route de Ceinture Sahloul, 4054, Sousse, Tunisia

    Rahma Kalboussi, Mehrez Abdellaoui & Ali Douik

  2. University of Sousse, Sousse, Tunisia

    Rahma Kalboussi, Mehrez Abdellaoui & Ali Douik

  3. Higher Institute of Computer Sciences and Communications Technology, Hammam Sousse, Sousse, Tunisia

    Rahma Kalboussi

Authors
  1. Rahma Kalboussi
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  2. Mehrez Abdellaoui
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  3. Ali Douik
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Corresponding authors

Correspondence to Rahma Kalboussi , Mehrez Abdellaoui or Ali Douik .

Editor information

Editors and Affiliations

  1. Istituto Di Calcolo E Reti Ad Alte Prestazioni (Icar), National Research Council, Roma, Italy

    Giuseppe De Pietro

  2. Istituto Di Calcolo E Reti Ad Alte Prestazioni (Icar), National Research Council, Roma, Italy

    Luigi Gallo

  3. Bournemouth University, Poole, United Kingdom

    Robert J. Howlett

  4. Centre for Artificial Intelligence, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, New South Wales, Australia

    Lakhmi C. Jain

  5. Griffith Sciences - Centres and Institutes, Griffith University, South Brisbane, Queensland, Australia

    Ljubo Vlacic

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Kalboussi, R., Abdellaoui, M., Douik, A. (2019). Local Saliency Estimation and Global Homogeneity Refinement for Video Saliency Detection. In: De Pietro, G., Gallo, L., Howlett, R., Jain, L., Vlacic, L. (eds) Intelligent Interactive Multimedia Systems and Services. KES-IIMSS-18 2018. Smart Innovation, Systems and Technologies, vol 98. Springer, Cham. https://doi.org/10.1007/978-3-319-92231-7_17

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