CASIA OpenIR  > 模式识别国家重点实验室  > 图像与视频分析
Joint image representation and classification in random semantic spaces
Zhang, Chunjie1; Zhu, Xiaobin2; Li, Liang1; Zhang, Yifan3; Liu, Jing3; Huang, Qingming1,4; Tian, Qi5
Source PublicationNEUROCOMPUTING
2015-05-25
Issue156Pages:79-85
SubtypeArticle
AbstractLocal feature based image representation has been widely used for image classification in recent years. Although this strategy has been proven very effective, the image representation and classification processes are relatively independent. This means the image classification performance may be hindered by the representation efficiency. To jointly consider the image representation and classification in an unified framework, in this paper, we propose a novel algorithm by combining image representation and classification in the random semantic spaces. First, we encode local features with the sparse coding technique and use the encoding parameters for raw image representation. These image representations are then randomly selected to generate the random semantic spaces and images are then mapped to these random semantic spaces by classifier training. The mapped semantic representation is then used as the final image representation. In this way, we are able to jointly consider the image representation and classification in order to achieve better performances. We evaluate the performances of the proposed method on several public image datasets and experimental results prove the proposed method's effectiveness. (C) 2015 Elsevier B.V. All rights reserved.
KeywordImage Representation Image Classification Semantic Space Random Sampling Sparse Representation
WOS HeadingsScience & Technology ; Technology
WOS KeywordFEATURES ; DESCRIPTORS
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000351978100009
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/10000
Collection模式识别国家重点实验室_图像与视频分析
Affiliation1.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing 100049, Peoples R China
2.Beijing Technol & Business Univ, Beijing, Peoples R China
3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
4.Chinese Acad Sci, Inst Comp Technol, Key Lab Intell Info Proc, Beijing 100190, Peoples R China
5.Univ Texas San Antonio, Dept Comp Sci, San Antonio, TX 78249 USA
Recommended Citation
GB/T 7714
Zhang, Chunjie,Zhu, Xiaobin,Li, Liang,et al. Joint image representation and classification in random semantic spaces[J]. NEUROCOMPUTING,2015(156):79-85.
APA Zhang, Chunjie.,Zhu, Xiaobin.,Li, Liang.,Zhang, Yifan.,Liu, Jing.,...&Tian, Qi.(2015).Joint image representation and classification in random semantic spaces.NEUROCOMPUTING(156),79-85.
MLA Zhang, Chunjie,et al."Joint image representation and classification in random semantic spaces".NEUROCOMPUTING .156(2015):79-85.
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