2.5d facial attractiveness computation based on data-driven geometric ratios

Shu Liu, Yangyu Fan, Zhe Guo, Ashok Samal

科研成果: 书/报告/会议事项章节会议稿件同行评审

9 引用 (Scopus)

摘要

Computational approaches to investigating face attractiveness have become an emerging topic in facial analysis research. Integrating techniques from image analysis, pattern recognition and machine learning, this subarea aims to explore the nature, components and impacts of facial attractiveness and to develop computational algorithms to analyze the attractiveness of a face. In this paper we develop an attractiveness computation model for both frontal and profile images (2.5D). We focus on the role of geometric ratios in the determination of facial attractivenss. Stepwise regression is used as the feature selection method to select the discriminatory variables from a huge set of data-driven ratios. Decision tree is then used to generate an automated classifier for both frontal and profile computation models. The BJUT-3D Face Database is pre-processed and tested as our experimental dataset. The low statistic errors and high correlation indicate the accuracy of our computation models.

源语言英语
主期刊名Intelligence Science and Big Data Engineering
主期刊副标题Image and Video Data Engineering - 5th International Conference, IScIDE 2015, Revised Selected Papers
编辑Xiaofei He, Zhi-Hua Zhou, Xinbo Gao, Zhi-Yong Liu, Yanning Zhang, Baochuan Fu, Fuyuan Hu, Zhancheng Zhang
出版商Springer Verlag
564-573
页数10
ISBN(印刷版)9783319239873
DOI
出版状态已出版 - 2015
活动5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015 - Suzhou, 中国
期限: 14 6月 201516 6月 2015

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
9242
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015
国家/地区中国
Suzhou
时期14/06/1516/06/15

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