Saliency Detection Based on Integration of Boundary and Soft-Segmentation

View Researcher's Other Codes

Disclaimer: The provided code links for this paper are external links. Science Nest has no responsibility for the accuracy, legality or content of these links. Also, by downloading this code(s), you agree to comply with the terms of use as set out by the author(s) of the code(s).

Authors Jing Sun, Huchuan Lu, and Shifeng Li
Journal/Conference Name International Conference on Image Processing
Paper Category
Paper Abstract Detection of the visual salient regions is a challenging and significant problem in computer vision. In this paper, we propose a boundary based prior map and a soft-segmentation based convex hull to improve the saliency detection. First, we present to utilize the boundary information to obtain the coarse prior map. Then a convex hull improved by soft-segmentation is proposed to form the observation likelihood map. Finally, the Bayes formula is applied to combine these two maps. Experiments on a publicly available database show that our augmented framework performs favorably against the state-of-the-art algorithms.
Date of publication 2012
Code Programming Language MATLAB

Copyright Researcher 2022