This report details a procedure for generating a computational model of facial expressions. This is a growing and relatively new type of problem within computer vision. One of the fundamental problems when trying to develop a computational model of facial expression in previous approaches is the lack of a consistent method of measuring expression. This report solves this problem by the computat...

1. Locating faces in the scene (e.g., in an image; this step is also referred to as face detection), 2. Extracting facial features from the detected face region (e.g., detecting the shape of facial components or describing the texture of the skin in a facial area; this step is referred to as facial feature extraction), 3. Analyzing the motion of facial features and/or the changes in the appeara...

Recent empirical studies have found that schizophrenics exhibit diminished observable facial expressivity in response to emotional stimuli (e.g., Berenbaum and Oltmanns 1992; Kring et al 1993; Kring and Neale 1996) yet report experiencing similar levels of emotion as their normal counterparts; however, it remains unclear whether schizophrenics are completely unexpressive, or if they exhibit mor...

In current dialogue systems the use of speech as an input modality is common. But this modality is only one of those human beings use. In human–human interaction people use gestures to point or facial expressions to show their moods as well. To give modern systems a chance to read information from all modalities used by humans, these systems must have multimodal user interfaces. The SMARTKOM sy...

Facial expressions are visible signs of a person’s affective state, cognitive activity and personality. Humans can perform expression recognition with a remarkable robustness without conscious effort even under a variety of adverse conditions such as partially occluded faces, different appearances and poor illumination. Over the last two decades, the advances in imaging technology and ever incr...

This paper proposes a novel local feature descriptor, Local Directional Number Pattern (LDN), for face analysis: face and expression recognition. LDN encodes the directional information of the face’s textures (i.e., the texture’s structure) in a compact way, producing a more discriminative code than current methods. We compute the structure of each micro-pattern with the aid of a compass mask, ...

An approach to the analysis and representation of facial dynamics for recognition of facial expressions from image sequences is proposed. The algorithms we develop utilize optical ow computation to identify the directions of rigid and non-rigid motions that are caused by human facial expressions. A mid-level symbolic representation motivated by linguistic and psychological considerations is dev...

OBJECTIVE Visual search is an important attention process that precedes the information processing. Visual search also mediates the relationship between cognition function (attention) and social cognition (such as facial expression identification). However, the association between visual attention and social cognition in patients with schizophrenia remains unknown. The purposes of this study we...

Facial Expression is a key component in evaluating a person's feelings, intentions and characteristics. Facial Expression is an important part of human-computer interaction and has the potential to play an equal important role in humancomputer interaction. The aim of this paper is bring together two areas in which are Artificial Neural Network (ANN) and KNearest Neighbor (K-NN) applying for fac...

Facial motions convey personal characteristics and subtle emotional states. This paper presents a new framework to model facial motions of different people with multiple expression types from high resolution facial expression tracking data. We also provide a mechanism to animate subtle facial expressions based on video sequences. A conceptual motion manifold is used for a unified representation...