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...

Facial expression recognition in the wild is a very challenging task. We describe our work in static and continuous facial expression recognition in the wild. We evaluate the recognition results of gray deep features and color deep features, and explore the fusion of multimodal texture features. For the continuous facial expression recognition, we design two temporal–spatial dense scale-invaria...

Automatic Facial Expression Recognition has been an active topic in computer science for over two decades, in particular Facial Action Coding System (FACS) Action Unit (AU) detection and classification of a number of discrete emotion states from facial expressive imagery. Standardisation and comparability has received some attention; for instance, there exist a number of commonly used facial ex...

Probing emotional facial expression recognition with the adaptation paradigm is one way to investigate the processes underlying emotional face recognition. Previous research suggests that these processes are tuned to dynamic facial information (facial movement). Here we examined the tuning of processes involved in the recognition of emotional facial expressions to different sources of facial mo...

objective: no research has been conducted on facial emotional recognition on patients with borderline personality disorder (bpd) and schizotypal personality disorder (spd). the present study aimed at comparing facial emotion recognition in these patients with the general population. the neurocognitive processing of emotions can show the pathologic style of these 2 disorders.   method:   twenty ...

Emotional understanding and expression is a fundamental basis for human-computer interaction, and how to read the human mind through facial expression recognition technology has become a hot issue. Large dimension of image data, sample calibration difficulties, and small size training sample set make the efficient facial expression recognition task difficult. DBN (Deep Belief Network) achieves ...

This paper introduce the methods of facial expression recognition, and describe different methods of feature extraction in expression recognition, including the method based on geometric feature, the method based on feature face, the method based on wavelet analysis, more features fusion and combination method, and simple analysis of various methods. Look ahead to the future research emphasis a...

1077-3142/$ see front matter 2010 Elsevier Inc. A doi:10.1016/j.cviu.2010.12.001 ⇑ Corresponding author. E-mail addresses: [email protected] (S ac.uk (R. Bowden). Research into facial expression recognition has predominantly been applied to face images at frontal view only. Some attempts have been made to produce pose invariant facial expression classifiers. However, most of these atte...

Automatic facial expression recognition plays an important role in various application domains such as medical imaging, surveillance and human-robot interaction. This research presents a novel facial expression recognition system with modified Local Binary Patterns (LBP) for feature extraction and a modified firefly algorithm (FA) for feature optimization. First, in order to deal with illuminat...

Micro-expressions are facial expressions that are characterized by short durations, involuntary generation and low intensity, and they are regarded as unique cues revealing one’s hidden emotions. Although methods for the recognition of general facial expressions have been intensively investigated, little progress has been made in the automatic recognition of micro-expressions. To further facili...