Saliency Detection with Sparse Prototypes: An Approach Based on Multi-Dictionary Sparse Encoding
This paper proposes a bottom-up saliency detection algorithm based on multi-dictionary sparse recovery. Firstly, the SLIC algorithm is used to segment the image into superpixels in multilevel and atoms with a high background possibility are selected from the boundary superpixels to construct the mul...
Main Authors: | Wang Jun, Wu Zemin, Tian Chang, Hu Lei |
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Format: | Article |
Language: | English |
Published: |
EDP Sciences
2018-01-01
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Series: | MATEC Web of Conferences |
Online Access: | https://doi.org/10.1051/matecconf/201817603009 |
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