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

fYear

2009

fDate

Nov. 30 2009-Dec. 2 2009

Firstpage

1425

Lastpage

1429

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ISDA.2009.57

Filename

5363967

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2828090