Traditional face superresolution methods treat face images as 1D vectors and apply PCA on the set of these 1D vectors to learn the face subspace. Zhang et al [7] proposed Two-dire...
Maximum Margin Criterion (MMC) based Feature Extraction method is more efficient than LDA for calculating the discriminant vectors since it does not need to calculate the inverse ...
Wankou Yang, Jianguo Wang, Mingwu Ren, Jingyu Yang
Most clustering algorithms operate by optimizing (either implicitly or explicitly) a single measure of cluster solution quality. Such methods may perform well on some data sets bu...
We propose a method to improve the results of image search engines on the Internet to satisfy users who desire to see relevant images in the first few pages. The method re-ranks ...
Hilal Zitouni, Sare Gul Sevil, Derya Ozkan, Pinar ...
This paper identifies a novel feature space to address the problem of human face recognition from still images. This is based on the PCA space of the features extracted by a new m...