The two-dimensional Principal Component Analysis (2DPCA) is a robust method in face recognition. Much recent research shows that the 2DPCA is more reliable than the well-known PCA ...
The lack of eye contact in video conference degrades the user’s experience. This problem has been known and studied for many years. There are hardware-based solutions to the eye...
Many applications require tracking and recognition of multiple faces at distances, such as in video surveillance. Such a task, dealing with non-cooperative objects is more challeng...
Rong Liu, Xiufeng Gao, Rufeng Chu, XiangXin Zhu, S...
Feature extraction is among the most important problems in face recognition systems. In this paper, we propose an enhanced kernel discriminant analysis (KDA) algorithm called kern...
Conventional subspace learning-based face recognition aims to attain low recognition errors and assumes same loss from all misclassifications. In many real-world face recognition...