Now a day’s Facial Expression Recognition field is growing and playing important role in communication. Facial expression recognition is a prototype where both humans and computer underperforms. It has great significance for the classification of video based management and video retrieval. It may be using in behaviour science and psychologist. There are many methods which is used to recognized ...

The Facial Action Coding System (FACS) [Ekman et al., 2002] is the leading method for measuring facial movement in behavioral science. FACS has been successfully applied, but not limited to, identifying the differences between simulated and genuine pain, differences betweenwhen people are telling the truth versus lying, and differences between suicidal and non-suicidal patients [Ekman and Rosen...

Parkinson's disease (PD) has been frequently associated with facial emotion recognition impairments, which could adversely affect the social functioning of those patients. Facial emotion recognition requires processing of the spatial relations between facial features, known as the facial configuration. Few studies, however, have investigated this ability in people with PD. We hypothesized that ...

We introduce a linear regression-based projection for multi-view facial expressions recognition (MFER) based on sparse features. While facial expression recognition (FER) approaches have become popular in frontal or near to frontal views, few papers demonstrate their results on arbitrary views of facial expressions. Our model relies on a new method for multi-view facial expression recognition, ...

Facial Expression is one of the most natural, and powerful means for human beings to Communicate their emotions and intentions. The recognition of facial expressions is very important for interactive Human Computer Interfaces. One crucial step for facial expression recognition (FER) is the accurate extraction of emotional features. Numerous feature extraction techniques have been developed for ...

An automatic face recognition system based on multiple facial features is described in this paper. Each facial feature is represented by a Gabor-based complex vector and is localized by an automatic facial feature detection scheme. Two face recognition approaches, named Two-Layer Nearest Neighbor (TLNN) and Modular Nearest Feature Line (MNFL) respectively, are proposed. Both TLNN and MNFL are b...

Deficits in facial emotion recognition in Parkinson's disease (PD) patients has been well documented. Nevertheless, it is still not clear whether facial emotion recognition deficits are secondary to other cognitive impairments. The aim of this study was to answer the question of whether deficits in facial emotion recognition in PD result from impaired sensory processes, or from impaired decisio...