| Image Class Prediction by Joint Object, Context, and Background Modeling | |
Zhang, Chunjie1,2,3 ; Zhu, Guibo4; Liang, Chao5; Zhang, Yifan6; Huang, Qingming2; Tian, Qi7
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| Source Publication | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
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| 2018-02-01 | |
| Volume | 28Issue:2Pages:428-438 |
| Subtype | Article |
| Abstract | State-of-the-art image classification methods often use spatial pyramid matching or its variants to make use of the spatial layout of visual features. However, objects may appear at various places with different scales and orientations. Besides, traditionally object-centric-based methods only consider objects and the background without fully exploring the context information. To solve these problems, in this paper we propose a novel image classification method by jointly modeling the object, context, and background information (OCB). OCB consists of three components: 1) locate the positions of objects; 2) determine the context areas of objects; and 3) treat the other areas as the background. We use objectness proposal techniques to select candidate bounding boxes. Boxes with high confidence scores are combined to determine objects' positions. To select the context areas, we use candidate boxes that have relatively lower confidence scores compared with boxes for object location selection. The other areas are viewed as the background. We jointly combine the object, context, and background for image representation and classification. Experiments on six data sets well demonstrate the superiority of the proposed OCB method over other spatial partition methods. |
| Keyword | Background Modeling Context Modeling Image Class Prediction Object Modeling |
| WOS Headings | Science & Technology ; Technology |
| DOI | 10.1109/TCSVT.2016.2613125 |
| WOS Keyword | CLASSIFICATION ; FEATURES |
| Indexed By | SCI |
| Language | 英语 |
| Funding Organization | National Natural Science Foundation of China(61303154) |
| WOS Research Area | Engineering |
| WOS Subject | Engineering, Electrical & Electronic |
| WOS ID | WOS:000425036400013 |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ia.ac.cn/handle/173211/15314 |
| Collection | 类脑智能研究中心 |
| Affiliation | 1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Key Lab Big Data Min & Knowledge Management, Beijing 100190, Peoples R China 4.Chinese Acad Sci, Res Ctr Brain Inspired Intelligence, Inst Automat, Beijing 100190, Peoples R China 5.Wuhan Univ, Natl Engn Res Ctr Multimedia Software, Sch Comp, Wuhan 430072, Hubei, Peoples R China 6.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China 7.Univ Texas San Antonio, Dept Comp Sci, San Antonio, TX 78249 USA |
| First Author Affilication | Institute of Automation, Chinese Academy of Sciences |
| Recommended Citation GB/T 7714 | Zhang, Chunjie,Zhu, Guibo,Liang, Chao,et al. Image Class Prediction by Joint Object, Context, and Background Modeling[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2018,28(2):428-438. |
| APA | Zhang, Chunjie,Zhu, Guibo,Liang, Chao,Zhang, Yifan,Huang, Qingming,&Tian, Qi.(2018).Image Class Prediction by Joint Object, Context, and Background Modeling.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,28(2),428-438. |
| MLA | Zhang, Chunjie,et al."Image Class Prediction by Joint Object, Context, and Background Modeling".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 28.2(2018):428-438. |
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| manuscript-object co（2826KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | View Download | |
| t-csvt 1 录用邮件.pdf（108KB） | 开放获取 | -- | View Download | |||
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