| Title | A Hybrid of Local and Global Saliencies for Detecting Image Salient Region and Appearance |
| Creator | |
| Date Issued | 2017 |
| Source Publication | IEEE Transactions on Systems, Man, and Cybernetics: Systems
 |
| ISSN | 2168-2216 |
| Volume | 47Issue:1Pages:86-97 |
| Abstract | This paper presents a visual saliency detection approach, which is a hybrid of local feature-based saliency and global feature-based saliency (simply called local saliency and global saliency, respectively, for short). First, we propose an automatic selection of smoothing parameter scheme to make the foreground and background of an input image more homogeneous. Then, we partition the smoothed image into a set of regions and compute the local saliency by measuring the color and texture dissimilarity in the smoothed regions and the original regions, respectively. Furthermore, we utilize the global color distribution model embedded with color coherence, together with the multiple edge saliency, to yield the global saliency. Finally, we combine the local and global saliencies, and utilize the composition information to obtain the final saliency. Experimental results show the efficacy of the proposed method, featuring: 1) the enhanced accuracy of detecting visual salient region and appearance in comparison with the existing counterparts, 2) the robustness against the noise and the low-resolution problem of images, and 3) its applicability to multisaliency detection task. |
| Keyword | Gradient minimization multiple salient edges saliency detection visual attention |
| DOI | 10.1109/TSMC.2016.2564922 |
| URL | View source |
| Language | 英语English |
| Scopus ID | 2-s2.0-85007493478 |
| Citation statistics | |
| Document Type | Journal article |
| Identifier | http://repository.uic.edu.cn/handle/39GCC9TT/6386 |
| Collection | Beijing Normal-Hong Kong Baptist University |
| Affiliation | 1.Department of Computer Science,Hong Kong Baptist University,Hong Kong,Hong Kong 2.United International College,Beijing Normal University-Hong Kong Baptist University,Zhuhai,519000,China 3.School of Electronic Information and Communications,Huazhong University of Science and Technology,Wuhan,430074,China 4.Department of Computer and Information Science,Faculty of Science and Technology,University of Macau,Macau,999078,Macao |
| Recommended Citation GB/T 7714 | Peng，Qinmu,Cheung，Yiu Ming,You，Xingeet al. A Hybrid of Local and Global Saliencies for Detecting Image Salient Region and Appearance[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017, 47(1): 86-97. |
| APA | Peng，Qinmu, Cheung，Yiu Ming, You，Xinge, & Tang，Yuan Yan. (2017). A Hybrid of Local and Global Saliencies for Detecting Image Salient Region and Appearance. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 47(1), 86-97. |
| MLA | Peng，Qinmu,et al."A Hybrid of Local and Global Saliencies for Detecting Image Salient Region and Appearance". IEEE Transactions on Systems, Man, and Cybernetics: Systems 47.1(2017): 86-97. |
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