Back to Search Start Over

Facial semantic descriptors based on information granules.

Authors :
Ren, Yan
Guan, Wei
Liu, Wanquan
Xi, Jianhui
Zhu, Linlin
Source :
Information Sciences. Apr2019, Vol. 479, p335-354. 20p.
Publication Year :
2019

Abstract

Abstract 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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00200255
Volume :
479
Database :
Academic Search Index
Journal :
Information Sciences
Publication Type :
Periodical
Accession number :
134253274
Full Text :
https://doi.org/10.1016/j.ins.2018.11.056