Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6938220 | Journal of Visual Communication and Image Representation | 2018 | 24 Pages |
Abstract
In this paper, we propose a novel visual saliency detection algorithm. The saliency of image region is defined as its global and local information. Firstly, we construct background-based map based on a novel multi-feature similarity metric by adjusting the weight of different features varied with image content, then integrated with center prior and Objectness measure into global saliency map. Secondly, a robust locality-based coding method is used to extract image local saliency cues by introducing effective codebooks selection rule and codebook element's reliability into reconstruction. Finally, we propose a novel integration mechanism to incorporate global and local saliency map for performance improvement. In terms of experimental results analysis on four benchmark datasets, the superiority of proposed algorithm is adequately demonstrated.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Ming Zhang, Yunhe Wu, Yue Du, Lei Fang, Yu Pang,