Title:

Fisher’s linear discriminant (FLD) and support vector machine (SVM) in non-negative matrix factorization (NMF) residual space for face recognition

Group publication title:

Optica Applicata

Creator:

Zhou, Changjun ; Wei, Xiaopeng ; Zhang, Qiang ; Fang, Xiaoyong

Contributor:

Gaj, Miron. Redakcja ; Urbańczyk, Wacław. Redakcja

Subject and Keywords:

optyka ; face recognition ; Fisher linear discriminant (FLD) ; non-negative matrix factorization (NMF) ; residual image

Description:

Optica Applicata, Vol. 40, 2010, nr 3, s. 693-704

Abstrakt:

A novel method of Fisher’s linear discriminant (FLD) in the residual space is put forward for the representation of face images for face recognition, which is robust to the slight local feature changes. The residual images are computed by subtracting the reconstructed images from the original face images, and the reconstructed images are obtained by performing non-negative matrix factorization (NMF) on original images. FLD is applied to the residual images for extracting FLD subspace and the corresponding coefficient matrices. Furthermore, features are obtained by mapping the residual image to FLD subspace. Finally, the features are utilized to train and test support vector machines (SVMs) for face recognition. The computer simulation illustrates that this method is effective on the ORL database and the extended Yale face database B.

Publisher:

Oficyna Wydawnicza Politechniki Wrocławskiej

Place of publication:

Wrocław

Date:

2010

Resource Type:

artykuł

Source:

<sygn. PWr A3481II> ; click here to follow the link ; click here to follow the link

Language:

eng

Relation:

Optica Applicata ; Optica Applicata, Vol. 40, 2010 ; Optica Applicata, Vol. 40, 2010, nr 3 ; Politechnika Wrocławska. Wydział Podstawowych Problemów Techniki

Rights:

Wszystkie prawa zastrzeżone (Copyright)

Access Rights:

Dla wszystkich w zakresie dozwolonego użytku

Location:

Politechnika Wrocławska