Contemporary face recognition algorithms rely on precise
localization of keypoints (corner of eye, nose etc.). Unfortunately,
finding keypoints reliably and accurately remains
a...
When applied to high-dimensional classification task such as face recognition, linear discriminant analysis (LDA) can extract two kinds of discriminant vectors, those in the null s...
Wangmeng Zuo, Kuanquan Wang, David Zhang, Jian Yan...
Soft biometric traits like gender, age, height, weight, ethnicity, and eye color cannot provide reliable user recognition because they are not distinctive and permanent. However, s...
Anil K. Jain, Karthik Nandakumar, Xiaoguang Lu, Un...
In this paper, a novel framework for the recovery of 3D surfaces of faces from single images is developed. The underlying principle is shape from recognition, i.e. the idea that p...
This paper presents a novel approach to face recognition, named Multi-resolution Histograms of Local Variation Patterns (MHLVP), in which face images are represented as the concate...