Hafiz, Fadhlan Kamaru Zaman and Shafie, Amir Akramin and Mohd. Mustafah, Yasir (2016) Robust face recognition against expressions and partial occlusions. International Journal of Automation and Computing, 13 (4). pp. 319-337. ISSN 1476-8186
PDF (Evidence from publishers' website for MYRA)
- Published Version
Restricted to Repository staff only Download (252kB) | Request a copy |
|
PDF (SCOPUS)
- Supplemental Material
Restricted to Repository staff only Download (138kB) | Request a copy |
Abstract
Facial features under variant-expressions and partial occlusions could have degrading effect on overall face recognition performance. As a solution, we suggest that the contribution of these features on final classification should be determined. In order to represent facial features’ contribution according to their variations, we propose a feature selection process that describes facial features as local independent component analysis (ICA) features. These local features are acquired using locally lateral subspace (LLS) strategy. Then, through linear discriminant analysis (LDA) we investigate the intraclass and interclass representation of each local ICA feature and express each feature’s contribution via a weighting process. Using these weights, we define the contribution of each feature at local classifier level. In order to recognize faces under single sample constraint, we implement LLS strategy on locally linear embedding (LLE) along with the proposed feature selection. Additionally, we highlight the efficiency of the implementation of LLS strategy. The overall accuracy achieved by our approach on datasets with different facial expressions and partial occlusions such as AR, JAFFE, FERET and CK+ is 90.70%. We present together in this paper survey results on face recognition performance and physiological feature selection performed by human subjects. © 2016, Institute of Automation, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg
Item Type: | Article (Journal) |
---|---|
Additional Information: | 5119/56447 |
Uncontrolled Keywords: | dimensionality reduction; Face recognition; facial expressions; feature selection; single sample |
Subjects: | T Technology > TA Engineering (General). Civil engineering (General) |
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Engineering Kulliyyah of Engineering > Department of Mechatronics Engineering |
Depositing User: | Dr Amir Shafie |
Date Deposited: | 12 Apr 2017 15:35 |
Last Modified: | 03 Jul 2017 10:35 |
URI: | http://irep.iium.edu.my/id/eprint/56447 |
Actions (login required)
View Item |