.png){kind=icon}
返回
Visual saliency detection with center shift
.png){kind=icon}
PRE
AI
DOI：10.1016/j.neucom.2012.08.029.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper proposes a novel method for visual saliency detection based on an universal probabilistic model, which measures the saliency by combining low level features and location prior. We view the task of estimating visual saliency as searching the most conspicuous parts in an image and extract the saliency map by computing the dissimilarity between different regions. We simulate the moving of the center of human visual field, and describe how the center shift process works on visual saliency. Furthermore, multiscale analysis is adopted for improving the robustness of our model. Experimental results on three public image datasets show that the proposed approach outperforms 18 state-of-the-art methods for both salient object detection and human eye fixation prediction. (C) 2012 Elsevier B.V. All rights reserved.
Keyword:
Visual saliency
Probabilistic model
Center shift
Multiscale analysis
Salient object
Human fixation
期刊
IF:
6.5
论文数:
2.5W
被引数:
6.5W
机构
引用论文
.png){kind=icon}
分享收藏Alumina based doped templated carbons: A comparative study with zeolite and silica gel templates
PREAI
分享收藏
查看更多内容