scholarly journals Research on Face Recognition Algorithm Based on Robust 2DPCA

2021 ◽  
Vol 11 (02) ◽  
pp. 149-161
Author(s):  
Haijun Kuang ◽  
Wanzhou Ye ◽  
Ze Zhu
Keyword(s):  
Face Recognition ◽  
Recognition Algorithm

Hybrid Face Recognition Algorithm for Wireless Sensor Network

2017 ◽  
Vol 13 (3) ◽  
pp. 267-281
Author(s):  
Matheel E. Abdulmunem E. Abdulmunem ◽  
◽  
Fatima B. Ibrahim
Keyword(s):  
Face Recognition ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Recognition Algorithm ◽  
Wireless Sensor

A Multi-angle Face Recognition Algorithm Based on Modified Gaussian Process Latent Variable Mode

2014 ◽  
Vol 35 (9) ◽  
pp. 2033-2039
Author(s):  
Jian Liu ◽  
Zhi-heng Gong ◽  
Cheng-dong Wu ◽  
En-yang Gao
Keyword(s):  
Face Recognition ◽  
Gaussian Process ◽  
Latent Variable ◽  
Recognition Algorithm ◽  
Variable Mode

Face Recognition Algorithm Based on Kernel Collaborative Representation

2013 ◽  
Vol 756-759 ◽  
pp. 3590-3595
Author(s):  
Liang Zhang ◽  
Ji Wen Dong
Keyword(s):  
Face Recognition ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Recognition Algorithm ◽  
Experimental Results ◽  
Collaborative Representation ◽  
Nonlinear Structures ◽  
Components Analysis ◽  
Kernel Principal Components Analysis ◽  
The Relationship

Aiming at solving the problems of occlusion and illumination in face recognition, a new method of face recognition based on Kernel Principal Components Analysis (KPCA) and Collaborative Representation Classifier (CRC) is developed. The KPCA can obtain effective discriminative information and reduce the feature dimensions by extracting faces nonlinear structures features, the decisive factor. Considering the collaboration among the samples, the CRC which synthetically consider the relationship among samples is used. Experimental results demonstrate that the algorithm obtains good recognition rates and also improves the efficiency. The KCRC algorithm can effectively solve the problem of illumination and occlusion in face recognition.

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