Performance of many state-of-the-art face recognition (FR) methods deteriorates rapidly, when large in size databases are considered. In this paper, we propose a novel clustering ...
Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes le...
Linear Discriminant Analysis (LDA) has been a popular method for feature extracting and face recognition. As a supervised method, it requires manually labeled samples for training...
Under the homoscedastic Gaussian assumption, it has been shown that Fisher’s linear discriminant analysis (FLDA) suffers from the class separation problem when the dimensionalit...
In this paper, a novel method based on pose adaptive linear discriminant analysis (PALDA) is proposed to deal with pose variation problems in face recognition when each person has...