CASIA OpenIR  > 模式识别国家重点实验室  > 视频内容安全
"Wow! You Are So Beautiful Today!"
Liu, Luoqi1; Xing, Junliang2; Liu, Si1; Xu, Hui3; Zhou, Xi3; Yan, Shuicheng1; Junliang Xing
Source PublicationACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS
2014-09-01
Volume11Issue:1Pages:1-22
SubtypeArticle
AbstractBeauty 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.
KeywordAlgorithms Experimentation Performance Beauty Recommendation Beauty Synthesis Multiple Tree-structured Super-graphs Model
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods
WOS IDWOS:000343984800012
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/8025
Collection模式识别国家重点实验室_视频内容安全
Corresponding AuthorJunliang Xing
Affiliation1.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
Recommended Citation
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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