Recently, studies of human face recognition have been conducted vigorously (Fasel & Luettin, 2003; Yang et al., 2002; Pantic & Rothkrantz, 2000a; Zhao et al., 2000; Hasegawa et al., 1997; Akamatsu, 1997). Such studies are aimed at the implementation of an intelligent man-machine interface. Especially, studies of facial expression recognition for humanmachine emotional communication are attracti...

PURPOSE The purpose of this study is to investigate peculiar patterns of facial asymmetry following incomplete recovery from facial paralysis that require optimal physical therapy for effective facial rehabilitation, and to decrease the incidence of avoidable facial sequelae. MATERIALS AND METHODS This study involved 41 patients who had facial sequelae following the treatment of various facia...

Personal identification of individuals is very important in forensic sciences. Facial identification is becoming even more relevant with increasing crime rates, problems with access control and terrorist attacks. To make facial identification more accurate, an in depth knowledge of the common and rare facial characteristics seen in various populations is needed. This will be advantageous when c...

Most automatic expression analysis systems attempt to recognize a small set of prototypic expressions, such as happiness, anger, surprise, and fear. Such prototypic expressions, however, occur rather infrequently. Human emotions and intentions are more often communicated by changes in one or a few discrete facial features. In this paper, we develop an Automatic Face Analysis (AFA) system to ana...

Facial features’ localization is a crucial step for many systems of face detection and facial expression recognition. It plays an essential role in human face analysis especially in searching for facial features (mouth, nose and eyes) when the face region is included within the image. The fundamental technique used in facial analysis is to detect the face and subsequently the associated salient...

Human facial gestures often exhibit such natural stochastic variations as how often the eyes blink, how often the eyebrows and the nose twitch, and how the head moves while speaking. The stochastic movements of facial features are key ingredients for generating convincing facial expressions. Although such small variations have been simulated using noise functions in many graphics applications, ...

Using faces representing exaggerated emotional expressions, recent behaviour and eye-tracking studies have suggested a dominant role of individual facial features in transmitting diagnostic cues for decoding facial expressions. Considering that in everyday life we frequently view low-intensity expressive faces in which local facial cues are more ambiguous, we probably need to combine expressive...

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...

The requirements for human face and facial features detection are motivated by various applications: face recognition, videoconferencing, and human computer interaction and security control are only a few examples. In this paper a novel face detection algorithm for color images is proposed in presence of varying lighting condition as well as complex background. Our algorithm detects eyes over t...