Facial Image Processing

Facial image processing is an area of research dedicated to the extraction and analysis of information about human faces; information which is known to play a central role in social interactions including recognition, emotion, and intention. Over the last decade, it has become a very active research field that deals with face detection and tracking, facial feature detection, face recognition, facial expression and emotion recognition, face coding, and virtual face synthesis. With the introduction of new powerful machine learning techniques, statistical classification methods, and complex deformable models, recent progresses have made possible a large number of applications in areas such as image retrieval, surveillance and biometrics, visual speech understanding , virtual characters for e-learning, online marketing or entertainment, intelligent human-computer interaction, and others. However, much remains to be done to provide more robust systems, especially when dealing with pose and illumination changes in complex natural scenes. If most approaches focus naturally on processing from still images, emerging techniques may also consider different inputs. For instance, video is becoming ubiquitous and very affordable, and there is a growing demand for vision-based human oriented applications, ranging from security to human computer interaction and video annotation. Capturing 3D data may as well become very affordable and processing such data can lead to enhanced systems, more robust to illumination effects and where discriminant information may be more easily retrieved. The scope of this special issue of the EURASIP Journal on Image and Video Processing is to present original contributions in the field of facial image processing, and especially on face verification and recognition, facial feature detection, face synthesis, and 3D face acquisition. Among the 20 submitted papers, six articles have been selected for this special issue. The paper by Arya and DiPaola addresses the construction of a behavioral face model for affective social agents based on three independent but interacting parameter spaces which are knowledge, personality, and mood. While a geometry space provides an MPEG-4 compatible set of parameters for low-level control, the behavioral extensions available through the triple spaces provide flexible means of designing complicated personality types, facial expression, and dynamic interactive scenarios. Robust facial feature detection for facial expression recognition in uncontrolled environments is the focus of investigation in the work presented by Ioannou et al. The proposed system is based on a multicue feature extraction and fusion technique, which provides MPEG-4-compatible features assorted with a confidence measure, used to weight their …