"Wow! You Are So Beautiful Today!"
文献类型：期刊论文
| 作者 | Liu, Luoqi1; Xing, Junliang2 ; Liu, Si1; Xu, Hui3; Zhou, Xi3; Yan, Shuicheng1; Junliang Xing
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| 刊名 | ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS
 |
| 出版日期 | 2014-09-01 |
| 卷号 | 11期号:1 |
| 关键词 | Algorithms Experimentation Performance Beauty recommendation beauty synthesis multiple tree-structured super-graphs model |
| 英文摘要 | 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. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods |
| 研究领域[WOS] | Computer Science |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000343984800012 |
| 公开日期 | 2015-09-22 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/8025]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_视频内容安全团队 |
| 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 |
| 推荐引用方式 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). |
| 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). |
| MLA | Liu, Luoqi,et al.""Wow! You Are So Beautiful Today!"".ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 11.1(2014). |
入库方式： OAI收割
来源：自动化研究所
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