CASIA OpenIR
Image Retargetability
Tang, Fan1,2; Dong, Weiming1; Meng, Yiping3; Ma, Chongyang4; Wu, Fuzhang5; Li, Xinrui6; Lee, Tong-Yee7
Source PublicationIEEE TRANSACTIONS ON MULTIMEDIA
ISSN1520-9210
2020-03-01
Volume22Issue:3Pages:641-654
Corresponding AuthorDong, Weiming(weiming.dong@ia.ac.cn)
AbstractReal-world applications could benefit from the ability to automatically retarget an image to different aspect ratios and resolutions while preserving its visually and semantically important content. However, not all images can be equally processed. This study introduces the notion of image retargetability to describe how well a particular image can be handled by content-aware image retargeting. We propose to learn a deep convolutional neural network to rank photo retargetability, in which the relative ranking of photo retargetability is directly modeled in the loss function. Our model incorporates the joint learning of meaningful photographic attributes and image content information, which can facilitate the regularization of the complicated retargetability rating problem. To train and analyze this model, we collect a dataset that contains retargetability scores and meaningful image attributes assigned by six expert raters. The experiments demonstrate that our unified model can generate retargetability rankings that are highly consistent with human labels. To further validate our model, we show the applications of image retargetability in retargeting method selection, retargeting method assessment and generating a photo collage.
KeywordVisualization Task analysis Distortion Measurement Image resolution Convolutional neural networks Semantics Image retargetability visual attributes multi-task learning deep convolutional neural network
DOI10.1109/TMM.2019.2932620
WOS KeywordOBJECTIVE QUALITY ASSESSMENT ; MODEL
Indexed BySCI
Language英语
Funding ProjectNational Key R&D Program of China[2018YFC0807500] ; National Natural Science Foundation of China[61832016] ; National Natural Science Foundation of China[61672520] ; National Natural Science Foundation of China[61702488] ; Ministry of Science and Technology, Taiwan[108-2221-E-006-038-MY3] ; CASIA-Tencent Youtu joint research project
Funding OrganizationNational Key R&D Program of China ; National Natural Science Foundation of China ; Ministry of Science and Technology, Taiwan ; CASIA-Tencent Youtu joint research project
WOS Research AreaComputer Science ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications
WOS IDWOS:000519576700006
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/38614
Collection中国科学院自动化研究所
Corresponding AuthorDong, Weiming
Affiliation1.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100864, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Didi Chuxing, Beijing 100094, Peoples R China
4.Kuaishou Technol, Beijing 100085, Peoples R China
5.Chinese Acad Sci, Inst Software, Beijing 100864, Peoples R China
6.North China Elect Power Univ, Dept Math & Phys, Beijing 102206, Peoples R China
7.Natl Cheng Kung Univ, Tainan 701, Taiwan
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Tang, Fan,Dong, Weiming,Meng, Yiping,et al. Image Retargetability[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2020,22(3):641-654.
APA Tang, Fan.,Dong, Weiming.,Meng, Yiping.,Ma, Chongyang.,Wu, Fuzhang.,...&Lee, Tong-Yee.(2020).Image Retargetability.IEEE TRANSACTIONS ON MULTIMEDIA,22(3),641-654.
MLA Tang, Fan,et al."Image Retargetability".IEEE TRANSACTIONS ON MULTIMEDIA 22.3(2020):641-654.
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