Abstract. Principal Component Analysis (PCA) plus Linear Discriminant Analysis (LDA) (PCA+LDA) and LDA/QR are both two-stage methods that deal with the small sample size (SSS) prob...
Illumination change is one of most important and difficult problems which prevent from applying face recognition to real applications. For solving this, we propose a method to comp...
Illumination invariance remains the most researched, yet the most challenging aspect of automatic face recognition. In this paper we investigate the discriminative power of colour...
This paper presents a technique for face recognition which uses wavelet transform to derive desirable facial features. Three level decompositions are used to form the pyramidal mul...
Dattatray V. Jadhav, Jayant V. Kulkarni, Raghunath...
Face recognition algorithms perform very unreliably when the pose of the probe face is different from the gallery face: typical feature vectors vary more with pose than with identi...
Simon J. D. Prince, James H. Elder, Jonathan Warre...