Saliency detection using joint spatial-color constraint and multi-scale segmentation

被引:41
作者
Xu, Linfeng [1 ]
Li, Hongliang [1 ]
Zeng, Liaoyuan [1 ]
King Ngi Ngan [2 ]
机构
[1] Univ Elect Sci & Technol China, Sch Elect Engn, Chengdu 611731, Peoples R China
[2] Chinese Univ Hong Kong, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China
基金
国家高技术研究发展计划(863计划);
关键词
Visual attention; Saliency model; Region detection; Human fixation prediction; Spatial constraint; Color double-opponent; Similarity distribution; Multi-scale technique; Segmentation-based method; VISUAL-ATTENTION; VIDEO; EXTRACTION; MODEL;
D O I
10.1016/j.jvcir.2013.02.007
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, a novel method is proposed to detect salient regions in images. To measure pixel-level saliency, joint spatial-color constraint is defined, i.e., spatial constraint (SC), color double-opponent (CD) constraint and similarity distribution (SD) constraint. The SC constraint is designed to produce global contrast with ability to distinguish the difference between "center and surround". The CD constraint is introduced to extract intensive contrast of red-green and blue-yellow double opponency. The SD constraint is developed to detect the salient object and its background. A two-layer structure is adopted to merge the SC, CD and SD saliency into a saliency map. In order to obtain a consistent saliency map, the region-based saliency detection is performed by incorporating a multi-scale segmentation technique. The proposed method is evaluated on two image datasets. Experimental results show that the proposed method outperforms the state-of-the-art methods on salient region detection as well as human fixation prediction. (c) 2013 Elsevier Inc. All rights reserved.
引用
收藏
页码:465 / 476
页数:12
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