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"Wow! You Are So Beautiful Today!"
Liu, Luoqi1; Xing, Junliang2; Liu, Si1; Xu, Hui3; Zhou, Xi3; Yan, Shuicheng1; Junliang Xing
2014-09-01
发表期刊ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS
卷号11期号:1页码:1-22
文章类型Article
摘要Beauty e-Experts, a fully automatic system for makeover recommendation and synthesis, is developed in this work. The makeover recommendation and synthesis system simultaneously considers many kinds of makeover items on hairstyle and makeup. Given a user-provided frontal face image with short/bound hair and no/light makeup, the Beauty e-Experts system not only recommends the most suitable hairdo and makeup, but also synthesizes the virtual hairdo and makeup effects. To acquire enough knowledge for beauty modeling, we built the Beauty e-Experts Database, which contains 1,505 female photos with a variety of attributes annotated with different discrete values. We organize these attributes into two different categories, beauty attributes and beauty-related attributes. Beauty attributes refer to those values that are changeable during the makeover process and thus need to be recommended by the system. Beauty-related attributes are those values that cannot be changed during the makeup process but can help the system to perform recommendation. Based on this Beauty e-Experts Dataset, two problems are addressed for the Beauty e-Experts system: what to recommend and how to wear it, which describes a similar process of selecting hairstyle and cosmetics in daily life. For the what-to-recommend problem, we propose a multiple tree-structured supergraph model to explore the complex relationships among high-level beauty attributes, mid-level beauty-related attributes, and low-level image features. Based on this model, the most compatible beauty attributes for a given facial image can be efficiently inferred. For the how-to-wear-it problem, an effective and efficient facial image synthesis module is designed to seamlessly synthesize the recommended makeovers into the user facial image. We have conducted extensive experiments on testing images of various conditions to evaluate and analyze the proposed system. The experimental results well demonstrate the effectiveness and efficiency of the proposed system.
关键词Algorithms Experimentation Performance Beauty Recommendation Beauty Synthesis Multiple Tree-structured Super-graphs Model
WOS标题词Science & Technology ; Technology
收录类别SCI
语种英语
WOS研究方向Computer Science
WOS类目Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods
WOS记录号WOS:000343984800012
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/8025
专题模式识别国家重点实验室_视频内容安全
通讯作者Junliang Xing
作者单位1.Natl Univ Singapore, Singapore 117548, Singapore
2.Chinese Acad Sci, Inst Automat, Beijing 100864, Peoples R China
3.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Beijing 100864, Peoples R China
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GB/T 7714
Liu, Luoqi,Xing, Junliang,Liu, Si,et al. "Wow! You Are So Beautiful Today!"[J]. ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,2014,11(1):1-22.
APA Liu, Luoqi.,Xing, Junliang.,Liu, Si.,Xu, Hui.,Zhou, Xi.,...&Junliang Xing.(2014)."Wow! You Are So Beautiful Today!".ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,11(1),1-22.
MLA Liu, Luoqi,et al.""Wow! You Are So Beautiful Today!"".ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 11.1(2014):1-22.
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