Title
Semantic description method for face features of larger Chinese ethnic groups based on improved WM method.
Abstract
In this paper, a semantic description method based on improved WM algorithm is proposed to characterize the facial features of larger Chinese ethnic groups. We firstly utilize the face landmarking technique to extract facial feature points automatically. Geometric features are defined with these detected landmarks, including distances, perimeters and areas. Then the WM method is improved to generate linguistic rule from facial geometric feature data, which implements semantic description for multi-ethnic facial characteristics. Finally, a case study of learning ethnicity from face with proposed method is investigated in CEFD database. The experiment results indicate that the linguistic rule base obtained by method is competitive in ethnicity recognition compared with method Naive Bayes, C4.5, Decision Table, Random Forest, Adaboost and Logistic regression in terms of accuracy and interpretability.
Year
DOI
Venue
2016
10.1016/j.neucom.2015.10.089
Neurocomputing
Keywords
Field
DocType
Chinese ethnic groups,Improved WM Method,Anthropometry,Morphology,Facial geometric features
Interpretability,Decision table,AdaBoost,Pattern recognition,Naive Bayes classifier,Computer science,Artificial intelligence,Ethnic group,Random forest,Feature data
Journal
Volume
ISSN
Citations 
175
0925-2312
5
PageRank 
References 
Authors
0.42
18
5
Name
Order
Citations
PageRank
Yuangang Wang1284.50
Duan Xiaodong28516.18
Xiaodong Liu350.42
Cun-rui Wang4195.21
Zedong Li5223.39