J
Jian Huang
Researcher at Hong Kong Baptist University
Publications - 15
Citations - 389
Jian Huang is an academic researcher from Hong Kong Baptist University. The author has contributed to research in topics: Linear discriminant analysis & Facial recognition system. The author has an hindex of 7, co-authored 14 publications receiving 369 citations.
Papers
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Journal ArticleDOI
Kernel machine-based one-parameter regularized Fisher discriminant method for face recognition
TL;DR: A new kernel machine-based one-parameter regularized Fisher discriminant technique based on the conjugate gradient method for face recognition that gives superior results compared with the existing LDA-based methods.
Journal ArticleDOI
Choosing Parameters of Kernel Subspace LDA for Recognition of Face Images Under Pose and Illumination Variations
TL;DR: An eigenvalue-stability-bounded margin maximization (ESBMM) algorithm is proposed to automatically tune the multiple parameters of the Gaussian radial basis function kernel for the kernel subspace LDA (KSLDA) method, which is developed based on the previously developed sub space LDA method.
Proceedings ArticleDOI
Kernel subspace LDA with optimized kernel parameters on face recognition
TL;DR: A new criterion is proposed and a new formation is derived in optimizing the parameters in RBF kernel based on the gradient descent algorithm to address the problem of selection of kernel parameters in kernel fisher discriminant for face recognition.
Proceedings ArticleDOI
Component-based LDA method for face recognition with one training sample
TL;DR: A component-based linear discriminant analysis (LDA) method to solve the one training sample problem of face recognition by constructing local facial feature component bunches by moving each local feature region in four directions.
Journal ArticleDOI
Face recognition using local and global features
TL;DR: This paper suggests a weighted combination of classifiers based on Kittler's combining classifier framework, and develops a simple but effective algorithm for classifiers selection.