Facial expression interpretation, recognition and analysis is a key issue in visual communication and man to machine interaction. In this paper, we present a factorization technique which decomposes the appearance parameters coding a natural image. This technique is then used to perform facial expression synthesis on unseen faces showing any undetermined facial expression, as well as facial exp...

We present a fully automatic system for 2D model-based image coding of human faces for potential applications such as video telephony, database image compression, and face recognition. The system operates by locating a face in the input image, normalizing its scale and geometry and representing it in terms of a parametric image model obtained with a Karhunen-Loeve basis. This leads to a compact...

Automatic facial image analysis is a long standing research problem in computer vision. A key component in facial image analysis, largely conditioning the success of subsequent algorithms (e.g. facial expression recognition), is to define a vocabulary of possible dynamic facial events. To date, that vocabulary has come from the anatomically based Facial Action Coding System (FACS) or taxonomies...

Automatic facial image analysis is a long standing research problem in computer vision. A key component in facial image analysis, largely conditioning the success of subsequent algorithms (e.g. facial expression recognition), is to define a vocabulary of possible dynamic facial events. To date, that vocabulary has come from the anatomically based Facial Action Coding System (FACS) or taxonomies...

We describe a deep learning based method for estimating 3D facial expression coefficients. Unlike previous work, our process does not relay on facial landmark detection methods as a proxy step. Recent methods have shown that a CNN can be trained to regress accurate and discriminative 3D morphable model (3DMM) representations, directly from image intensities. By foregoing facial landmark detecti...

Face Representation (FR) plays a typically important role in face recognition and methods such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) have been received wide attention recently. However, despite of the achieved successes, these FR methods will inevitably lead to poor classification performance in case of great facial variations such as expression, lighting,...

In this paper, the facial expression is mainly focused to achieve the smooth tele-communications. The facial expressions has been considered as a most of the signi cant factors in tele-communications, such as tele-services. To realize the real time facial expression transportation system, we proposed the facial expression space (FES) and a correspondence technique between each personal facial e...

This paper addresses the issue of 3-D motion estimation in model-based facial image coding. A new approach to estimating the motion of the head and the facial expressions is presented and has the following characteristics: 1) An affine nonrigid motion model is set up. The specific knowledge about facial shape and facial expression is formulated by this model in the form of parameters. This affi...

We present a component-based face descriptor with LDA (Linear Discriminant Analysis) and a simple pose classification. Our algorithm has been developed to deal with face image retrieval in huge database such as those in internet environments. Such retrieval requires a compact face descriptor and an efficient recognition algorithm that is robust to variations in lighting and facial poses. Partit...