Image Retargetability

doi:10.1109/TMM.2019.2932620

	Image Retargetability
	Tang, Fan1,2 ; Dong, Weiming1 ; Meng, Yiping3 ; Ma, Chongyang 4; Wu, Fuzhang 5; Li, Xinrui 6; Lee, Tong-Yee 7
发表期刊	IEEE TRANSACTIONS ON MULTIMEDIA
ISSN	1520-9210
	2020-03-01
卷号	22 期号:3 页码:641-654
通讯作者	Dong, Weiming(weiming.dong@ia.ac.cn)
摘要	Real-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.
关键词	Visualization Task analysis Distortion Measurement Image resolution Convolutional neural networks Semantics Image retargetability visual attributes multi-task learning deep convolutional neural network
DOI	10.1109/TMM.2019.2932620
关键词[WOS]	OBJECTIVE QUALITY ASSESSMENT ; MODEL
收录类别	SCI
语种	英语
资助项目	National 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
项目资助者	National 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研究方向	Computer Science ; Telecommunications
WOS类目	Computer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications
WOS记录号	WOS:000519576700006
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
七大方向——子方向分类	图像视频处理与分析
引用统计	被引频次：5[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/38614
专题	多模态人工智能系统全国重点实验室_多媒体计算
通讯作者	Dong, Weiming
作者单位	1.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
第一作者单位	模式识别国家重点实验室
通讯作者单位	模式识别国家重点实验室
推荐引用方式 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.