Abstract
In past decades, salient object detection has witnessed rapid progress. In this paper, we propose an efficient framework for salient object detection by considering background scatter and foreground contour completeness. First, the method utilizes boundary prior embedded with background scatter to yield the boundary contrast map (BCM). Then, a contour completeness map (CCM) is constructed using the completely closed shape of the object. Next, an adaptive fusion algorithm is designed to fuse both BCM and CCM. Finally, we develop a post-processing refinement for fused map to obtain the final saliency map. On three datasets, the proposed method significantly outperforms eights state-of-the-arts both quantitatively and qualitatively.
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Xia, C., Zhao, Q., Zhang, S., Gao, X. (2020). A Hybrid of Background Scatter and Foreground Contour Completeness for Salient Object Detection. In: Abawajy, J., Choo, KK., Islam, R., Xu, Z., Atiquzzaman, M. (eds) International Conference on Applications and Techniques in Cyber Intelligence ATCI 2019. ATCI 2019. Advances in Intelligent Systems and Computing, vol 1017. Springer, Cham. https://doi.org/10.1007/978-3-030-25128-4_158
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DOI: https://doi.org/10.1007/978-3-030-25128-4_158
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