Face recognition methods for multimodal interface

Author

Ban, Jozef ; Pavlovicova, Jarmila ; Feder, Meir ; Omelina, Lubes ; Oravec, Milos

Author_Institution

Inst. of Telecommun., Slovak Univ. of Technol., Bratislava, Slovakia

fYear

2012

fDate

19-21 Sept. 2012

Firstpage

110

Lastpage

113

Abstract

In this paper we provide a comparative study of several conventional face recognition methods (PCA, KPCA, GDA, SVM and RBF) that are suitable to work properly in multimodal systems. Performance of these systems is often influenced by various negative effects of the real-world environment. We evaluate the influence of varying illuminations and pose of faces on face recognition accuracy. Based on the results of our experiments we select the most suitable face recognition methods for application in HBB-NEXT project. This project wants to lay the foundations for advanced hybrid multiuser services.

Keywords

face recognition; human computer interaction; principal component analysis; radial basis function networks; support vector machines; GDA; HBB-NEXT project; KPCA; PCA; RBF; SVM; face recognition methods; generalized discriminant analysis; kernel principal component analysis; multimodal interface; multimodal systems; principal component analysis; radial basis function neural network; services; support vector machine; Databases; Face; Face recognition; Kernel; Lighting; Principal component analysis; Support vector machines; face recognition; machine learning methods; multimodal interface;

fLanguage

English

Publisher

ieee

Conference_Titel

Wireless and Mobile Networking Conference (WMNC), 2012 5th Joint IFIP

Conference_Location

Bratislava

Print_ISBN

978-1-4673-2993-4

Type

conf

DOI

10.1109/WMNC.2012.6416164

Filename

6416164