Title :
View-Independent Face Recognition with Biological Features Based on Mixture of Experts
Author :
Hajiany, Alireza ; Makhsoos, Nina Taheri ; Ebrahimpour, Reza
Author_Institution :
Electr. & Comput. Eng., Shahid Rajaee Univ., Tehran, Iran
fDate :
Nov. 30 2009-Dec. 2 2009
Abstract :
The proposed view-independent face recognition model based on mixture of expert, ME, uses feature extraction, C1 standard model feature, C1 SMF, motivated from biology on the CMU PIE dataset. The strength of the proposed model is using fewer training data as well as attaining high recognition rate since C1 standard model feature and the combining method based on ME were jointly used.
Keywords :
face recognition; feature extraction; medical image processing; C1 standard model feature; biological features; feature extraction; high recognition rate; standard model feature; view-independent face recognition; Biological system modeling; Biology computing; Brain modeling; Computational modeling; Data engineering; Design engineering; Face recognition; Feature extraction; Intelligent systems; Object recognition; C1 Standard Model Feature; CMU PIE dataset; Mixture of Expert; view-independent face recognition;
Conference_Titel :
Intelligent Systems Design and Applications, 2009. ISDA '09. Ninth International Conference on
Conference_Location :
Pisa
Print_ISBN :
978-1-4244-4735-0
Electronic_ISBN :
978-0-7695-3872-3
DOI :
10.1109/ISDA.2009.57
