This paper presents a meta-analysis for covariates that affect performance of face
recognition algorithms. Our review of the literature found six covariates for which multiple …

Automatic facial expression analysis is an interesting and challenging problem, and impacts
important applications in many areas such as human–computer interaction and data-driven …

In this paper, we define meta-recognition, a performance prediction method for recognition
algorithms, and examine the theoretical basis for its postrecognition score analysis form …

This paper presents a new face recognition algorithm based on the well-known EBGM which
replaces Gabor features by HOG descriptors. The recognition results show a better …

摘! 要! 利用典型相关分析的思想& 提出了一种基于特征级融合的组合特征抽取新方法9 首先&
探讨了将典型分析用于模式识别的理论构架& 给出了其合理的描述9 即先抽取同一模式的两组 …

Scale invariant feature transform (SIFT) proposed by Lowe has been widely and
successfully applied to object detection and recognition. However, the representation ability …

Face verification, though an easy task for humans, is a long-standing open research area.
This is largely due to the challenging covariates, such as disguise and aging, which make it …

In this work, we propose a novel approach to recognize facial expressions from static
images. First, the local binary patterns (LBP) are used to efficiently represent the facial …

Because of its nonrigidity and complex three-dimensional (3D) structure, the appearance of
a face is affected by a large number of factors including identity, face pose, illumination …

Face recognition has made significant advances in the last decade, but robust commercial
applications are still lacking. Current authentication/identification applications are limited to …