CASIA OpenIR  > 模式识别国家重点实验室  > 图像与视频分析
Adaptive Content Condensation Based on Grid Optimization for Thumbnail Image Generation
Wang, Jinqiao1; Qu, Zhan2; Chen, Yingying1; Mei, Tao3; Xu, Min4; Zhang, La1; Lu, Hanqing1; Jinqiao Wang
Source PublicationIEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
2016-11-01
Volume26Issue:11Pages:2079-2092
SubtypeArticle
AbstractAn ideal thumbnail generator should effectively condense unimportant regions and keep the important content undeformed, completed, and at a proper scale, i.e., accuracy, completeness, and sufficiency. Each retargeting method has its own advantage for resizing arbitrary images. However, they often ignore the completeness and sufficiency for information presentation in thumbnails. In this paper, we formulate thumbnail generation as an image content condensation problem and propose a unified grid optimization framework to fuse multiple operators. From the view of accuracy, completeness, and sufficiency for information presentation, we exploit complementary relationships among three condensation operators and fuse them into a unified grid-based convex programming problem, which could be solved simultaneously and efficiently through numerical optimization. Besides warping energy to preserve the geometric structure of important objects, we put forward two grid-based energy terms to keep the completeness of important objects and retain them at a proper size. Finally, an adaptive procedure is proposed to dynamically adjust the contribution of loss functions for achieving optimal content condensation. Both qualitative and quantitative comparison results demonstrate that the proposed method achieves an excellent tradeoff among accuracy, completeness, and sufficiency of information preservation. The experimental results show that our approach is obviously superior to the state-of-the-art techniques.
KeywordImage Browsing Image Resizing Image Retargeting Thumbnail Generation
WOS HeadingsScience & Technology ; Technology
DOI10.1109/TCSVT.2015.2493500
WOS KeywordSALIENT REGION DETECTION ; QUALITY ASSESSMENT ; MODEL
Indexed BySCI
Language英语
Funding Organization863 Program(2014AA015104) ; National Natural Science Foundation of China(61273034 ; 61332016)
WOS Research AreaEngineering
WOS SubjectEngineering, Electrical & Electronic
WOS IDWOS:000387894100008
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/11073
Collection模式识别国家重点实验室_图像与视频分析
Corresponding AuthorJinqiao Wang
Affiliation1.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China
2.Huawei Technol Co Ltd, Media Lab, Shenzhen 518129, Peoples R China
3.Microsoft Res Asia, Beijing 100080, Peoples R China
4.Univ Technol Sydney, Global Big Data Technol Ctr, Sydney, NSW 2007, Australia
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Wang, Jinqiao,Qu, Zhan,Chen, Yingying,et al. Adaptive Content Condensation Based on Grid Optimization for Thumbnail Image Generation[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2016,26(11):2079-2092.
APA Wang, Jinqiao.,Qu, Zhan.,Chen, Yingying.,Mei, Tao.,Xu, Min.,...&Jinqiao Wang.(2016).Adaptive Content Condensation Based on Grid Optimization for Thumbnail Image Generation.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,26(11),2079-2092.
MLA Wang, Jinqiao,et al."Adaptive Content Condensation Based on Grid Optimization for Thumbnail Image Generation".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 26.11(2016):2079-2092.
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