Abstract. Recently in face recognition, as opposed to our expectation, the performance of an ICA (Independent Component Analysis) method combined with LDA (Linear Discriminant Analysis) was reported as lower than an ICA only based method. This research points out that (ICA+LDA) methods have not got a fair comparison for evaluating its recognition performance. In order to incorporate class specific information into ICA, we have employed FLD (Fisher Linear Discriminant) and have proposed our (ICA+FLD) method. In the experimental results, we report that our (ICA+FLD) method has better performance than ICA only based methods as well as other representative methods such as Eigenface and Fisherface methods. 1
Principal Component Analysis (PCA) has emerged as a more efficient approach for extracting features ...
This paper presents a subspace algorithm called block independent component analysis (B-ICA) for fac...
Linear Discriminant Analysis (LDA) has been successfully applied to face recognition which is based ...
Face recognition is used in wide range of application. In recent years, face recognition has become ...
In this paper, the performances of appearance-based statistical methods such as Principal Component ...
Recognizing Faces with PCA and ICA This paper compares principal component analysis (PCA) and indepe...
Abstract: In this paper two Face Recognition techniques, Principal Component Analysis (PCA) and Line...
Abstract—The literature on independent component analysis (ICA)-based face recognition generally eva...
Abstract: A comparative recognition performance of LDA- and ICA-based multiple classifier systems fo...
Face recognition is emerging as an active research area with numerous commercial and law enforcement...
Abstract – In this research, we show how the promising Independent Component Analysis (ICA) techniqu...
This study investigates a new method of feature extraction for classification prob-lems. The method ...
In this thesis, we present a comparative study among some of the existing major approaches for human...
Nowadays, face recognition is used in number of applications as a means of authentication and verifi...
Face recognition system should be able to automatically detect a face in images. This involves extra...
Principal Component Analysis (PCA) has emerged as a more efficient approach for extracting features ...
This paper presents a subspace algorithm called block independent component analysis (B-ICA) for fac...
Linear Discriminant Analysis (LDA) has been successfully applied to face recognition which is based ...
Face recognition is used in wide range of application. In recent years, face recognition has become ...
In this paper, the performances of appearance-based statistical methods such as Principal Component ...
Recognizing Faces with PCA and ICA This paper compares principal component analysis (PCA) and indepe...
Abstract: In this paper two Face Recognition techniques, Principal Component Analysis (PCA) and Line...
Abstract—The literature on independent component analysis (ICA)-based face recognition generally eva...
Abstract: A comparative recognition performance of LDA- and ICA-based multiple classifier systems fo...
Face recognition is emerging as an active research area with numerous commercial and law enforcement...
Abstract – In this research, we show how the promising Independent Component Analysis (ICA) techniqu...
This study investigates a new method of feature extraction for classification prob-lems. The method ...
In this thesis, we present a comparative study among some of the existing major approaches for human...
Nowadays, face recognition is used in number of applications as a means of authentication and verifi...
Face recognition system should be able to automatically detect a face in images. This involves extra...
Principal Component Analysis (PCA) has emerged as a more efficient approach for extracting features ...
This paper presents a subspace algorithm called block independent component analysis (B-ICA) for fac...
Linear Discriminant Analysis (LDA) has been successfully applied to face recognition which is based ...