Detecting and recognizing human faces automatically in digital images strongly enhance
content-based video indexing systems. In this paper, a novel scheme for human faces …

This paper is a comparative study of three recently proposed algorithms for face recognition:
eigenface, autoassociation and classification neural nets, and elastic matching. After these …

Sparse representation (or coding)-based classification (SRC) has gained great success in
face recognition in recent years. However, SRC emphasizes the sparsity too much and …

An approach to the analysis and representation of facial dynamics for recognition of facial
expressions from image sequences is presented. The algorithms utilize optical flow …

Automatic retrieval of face images from police mug-shot databases is critically important for
law enforcement agencies. It can effectively help investigators to locate or narrow down …

The automatic recognition of human faces presents a significant challenge to the pattern
recognition research community. Typically, human faces are very similar in structure with …

We describe the use of flexible models for representing the shape and grey-level
appearance of human faces. These models are controlled by a small number of parameters …

Evaluations of the state-of-the-art of both academic face recognition algorithms and
commercial systems have shown that recognition performance of most current technologies …

Feature extraction, discriminant analysis, and classification rules are three crucial issues for
face recognition. We present hybrid approaches to handle three issues together. For feature …

Abstract Convolutional Sparse Coding (CSC) is an increasingly popular model in the signal
and image processing communities, tackling some of the limitations of traditional patch …