We propose an appearance-based face recognition method called the Laplacianface
approach. By using locality preserving projections (LPP), the face images are mapped into a …

Following the intuition that the naturally occurring face data may be generated by sampling a
probability distribution that has support on or near a submanifold of ambient space, we …

There is a growing interest in subspace learning techniques for face recognition; however,
the excessive dimension of the data space often brings the algorithms into the curse of …

In many computer vision tasks like face recognition and image retrieval, one is often
confronted with high-dimensional data. Procedures that are analytically or computationally …

In this paper, we propose an L1-norm two-dimensional linear discriminant analysis (L1-
2DLDA) with robust performance. Different from the conventional two-dimensional linear …

Disentangled representation learning finds compact, independent and easy-to-interpret
factors of the data. Learning such has been shown to require an inductive bias, which we …

This paper aims to deploy a network that consists a group of computers connected with a
microcomputer with a camera. The system takes images of people, analyze, detect and …

The appearance of a face will vary drastically when the illumination changes. Variations in
lighting conditions make face recognition an even more challenging and difficult task. In this …

A method and apparatus for recognizing and searching for a face using 2nd-order
independent component analysis (ICA) are provided. The method for describing feature …

In many computer vision applications, images are acquired with arbitrary or random
rotations and translations, and in such setups, it is desirable to obtain semantic …