In this paper, a new technique for modeling textured 3D faces is introduced. 3D faces can
either be generated automatically from one or more photographs, or modeled directly …

We present an example-based learning approach for locating vertical frontal views of human
faces in complex scenes. The technique models the distribution of human face patterns by …

Abstract Machine learning has not yet succeeded in the design of robust learning algorithms
that generalize well from very small datasets. In contrast, humans often generalize correctly …

The facial action coding system (FAGS) is an objective method for quantifying facial
movement in terms of component actions. This paper explores and compares techniques for …

In this paper, we propose a novel method, called local non-negative matrix factorization
(LNMF), for learning spatially localized, parts-based subspace representation of visual …

In this paper, we present a neural network-based face detection system. Unlike similar
systems which are limited to detecting upright, frontal faces, this system detects faces at any …

Facial expressions provide an important behavioral measure for the study of emotion,
cognitive processes, and social interaction. The Facial Action Coding System (Ekman & …

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 …

One of the key problems in supervised learning is the insufficient size of the training set. The
natural way for an intelligent learner to counter this problem and successfully generalize is …

This paper explores the use of local parametrized models of image motion for recovering
and recognizing the non-rigid and articulated motion of human faces. Parametric flow …