Image Categorization by Learning a Propagated Graphlet Path

CORC > 西安光学精密机械研究所 > 中国科学院西安光学精密机械研究所 > 光学影像学习与分析中心

	Image Categorization by Learning a Propagated Graphlet Path
	Zhang, Luming 1; Hong, Richang 1; Gao, Yue 2; Ji, Rongrong 3; Dai, Qionghai 2; Li, Xuelong4
刊名	ieee transactions on neural networks and learning systems
	2016-03-01
卷号	27 期号:3 页码:674-685
关键词	Feature learning image categorization manifold embedding object shaped propagation
ISSN号	2162-237x
产权排序	4
英文摘要	spatial pyramid matching is a standard architecture for categorical image retrieval. however, its performance is largely limited by the prespecified rectangular spatial regions when pooling local descriptors. in this paper, we propose to learn object-shaped and directional receptive fields for image categorization. in particular, different objects in an image are seamlessly constructed by superpixels, while the direction captures human gaze shifting path. by generating a number of superpixels in each image, we construct graphlets to describe different objects. they function as the object-shaped receptive fields for image comparison. due to the huge number of graphlets in an image, a saliency-guided graphlet selection algorithm is proposed. a manifold embedding algorithm encodes graphlets with the semantics of training image tags. then, we derive a manifold propagation to calculate the postembedding graphlets by leveraging visual saliency maps. the sequentially propagated graphlets constitute a path that mimics human gaze shifting. finally, we use the learned graphlet path as receptive fields for local image descriptor pooling. the local descriptors from similar receptive fields of pairwise images more significantly contribute to the final image kernel. thorough experiments demonstrate the advantage of our approach.
学科主题	计算机应用其他学科（含图像处理）
WOS标题词	science & technology ; technology
类目[WOS]	computer science, artificial intelligence ; computer science, hardware & architecture ; computer science, theory & methods ; engineering, electrical & electronic
研究领域[WOS]	computer science ; engineering
关键词[WOS]	object recognition ; mean shift ; machines
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:000372022900014
内容类型	期刊论文
源URL	[http://ir.opt.ac.cn/handle/181661/27893]
专题	西安光学精密机械研究所_光学影像学习与分析中心
作者单位	1.Hefei Univ Technol, Dept Elect Engn & Informat Syst, Hefei 230009, Peoples R China 2.Tsinghua Univ, Beijing 100084, Peoples R China 3.Xiamen Univ, Sch Informat Sci & Engn, Dept Cognit Sci, Xiamen 361006, Peoples R China 4.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr OPT IMagery Anal & Learning, Xian 710119, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Luming,Hong, Richang,Gao, Yue,et al. Image Categorization by Learning a Propagated Graphlet Path[J]. ieee transactions on neural networks and learning systems,2016,27(3):674-685.
APA	Zhang, Luming,Hong, Richang,Gao, Yue,Ji, Rongrong,Dai, Qionghai,&Li, Xuelong.(2016).Image Categorization by Learning a Propagated Graphlet Path.ieee transactions on neural networks and learning systems,27(3),674-685.
MLA	Zhang, Luming,et al."Image Categorization by Learning a Propagated Graphlet Path".ieee transactions on neural networks and learning systems 27.3(2016):674-685.