Facial semantic descriptors based on information granules
Facial semantic descriptors based on information granules
复制标题
基于信息粒的面部语义描述子
DOI：
10.1016/j.ins.2018.11.056
复制
发表时间：
2019
影响因子：
8.1
通讯作者：
Zhu Linlin
中科院分区：
文献类型：
--
作者：
Ren Yan;Guan Wei;Liu Wanquan;Xi Jianhui;Zhu Linlin
在本文中，我们研究了面部成分的粒度数据描述，其中面部成分的特征由信息颗粒的集合呈现。首先，利用面部标志检测器自动提取面部成分。其次，基于这些检测到的标志，通过涉及各种模糊聚类机制来形成语义概念。可以寻找数字原型的集合作为描述符的蓝图。因此，信息颗粒是围绕粒度计算的基本思想（特别是合理粒度原则）所涉及的原型形成的。在Multi-PIE人脸数据库上的多次实验表明，所提出的基于信息粒的人脸语义描述符不仅可以表征数据中人脸成分的关键语义，而且与人类感知相比可以提高语义分类性能。
In this paper, we investigate a granular data description for facial components in which a characterization of facial components is presented by a collection of information granules. Firstly, the facial landmark detector is utilized to extract facial components automatically. Secondly, semantic concepts are formed by involving various mechanisms of fuzzy clustering based on these detected landmarks. A collection of numeric prototypes can be sought as a blueprint of the descriptors. Consequently, the information granules are being formed around the prototypes that are engaged by the fundamental ideas of Granular Computing, especially the principle of justifiable granularity. Multiple experiments on Multi-PIE facial database illustrate the proposed facial semantic descriptors based on information granules not only can characterize the key semantics of facial components of data, but also can improve the semantic classification performance in comparison with human perception.