Salient region detection and segmentation for general object recognition and image understanding

doi:10.1007/s11432-011-4487-1

	Salient region detection and segmentation for general object recognition and image understanding
	Huang TieJun 1; Tian YongHong 1; Li Jia 2; Yu HaoNan 1
	2011-12-01
发表期刊	SCIENCE CHINA-INFORMATION SCIENCES
ISSN	1674-733X
卷号	54 期号:12 页码:2461-2470
摘要	General object recognition and image understanding is recognized as a dramatic goal for computer vision and multimedia retrieval. In spite of the great efforts devoted in the last two decades, it still remains an open problem. In this paper, we propose a selective attention-driven model for general image understanding, named GORIUM (general object recognition and image understanding model). The key idea of our model is to discover recurring visual objects by selective attention modeling and pairwise local invariant features matching on a large image set in an unsupervised manner. Towards this end, it can be formulated as a four-layer bottomup model, i.e., salient region detection, object segmentation, automatic object discovering and visual dictionary construction. By exploiting multi-task learning methods to model visual saliency simultaneously with the bottom-up and top-down factors, the lowest layer can effectively detect salient objects in an image. The second layer exploits a simple yet effective learning approach to generate two complementary maps from several raw saliency maps, which then can be utilized to segment the salient objects precisely from a complex scene. For the third layer, we have also implemented an unsupervised approach to automatically discover general objects from large image set by pairwise matching with local invariant features. Afterwards, visual dictionary construction can be implemented by using many state-of-the-art algorithms and tools available nowadays.
关键词	object recognition image understanding visual saliency salient object segmentation visual dictionary
DOI	10.1007/s11432-011-4487-1
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[90820003] ; National Natural Science Foundation of China[60973055] ; National Basic Research Program of China[2009CB320906] ; Ministry of Education of China
WOS研究方向	Computer Science
WOS类目	Computer Science, Information Systems
WOS记录号	WOS:000297709400002
出版者	SCIENCE PRESS
引用统计	被引频次：18[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/12776
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Tian YongHong
作者单位	1.Peking Univ, Sch Elect Engn & Comp Sci, Natl Engn Lab Video Technol, Beijing 100871, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Huang TieJun,Tian YongHong,Li Jia,et al. Salient region detection and segmentation for general object recognition and image understanding[J]. SCIENCE CHINA-INFORMATION SCIENCES,2011,54(12):2461-2470.
APA	Huang TieJun,Tian YongHong,Li Jia,&Yu HaoNan.(2011).Salient region detection and segmentation for general object recognition and image understanding.SCIENCE CHINA-INFORMATION SCIENCES,54(12),2461-2470.
MLA	Huang TieJun,et al."Salient region detection and segmentation for general object recognition and image understanding".SCIENCE CHINA-INFORMATION SCIENCES 54.12(2011):2461-2470.