All the traditional PCA-based and LDA-based methods are based on the analysis of vectors. So, it is difficult to evaluate the covariance matrices in such a high-dimensional vector ...
Face recognition degrades when faces are of very low resolution since many details about the difference between one person and another can only be captured in images of sufficient...
Pablo H. Hennings-Yeomans, Simon Baker, B. V. K. V...
A feature extraction method using multi-frequency bands is proposed for face recognition, named as the Multi-band Gradient Component Pattern (MGCP). The MGCP captures discriminativ...
Yimo Guo, Jie Chen, Guoying Zhao, Matti Pietik&aum...
This paper presents a novel and interesting combination of wavelet techniques and eigenfaces to extract features for face recognition. Eigenfaces reduce the dimensions of face vec...
Recently, we proposed a fast feature extraction approach denoted FSOM utilizes Self Organizing Map (SOM). FSOM [1] overcomes the slowness of traditional SOM search algorithm. We i...
Alaa El. Sagheer, Naoyuki Tsuruta, Rin-ichiro Tani...