The current study examined the nature of deficits in emotion recognition from facial expressions in case LG, an individual with a rare form of developmental visual agnosia (DVA). LG presents with profoundly impaired recognition of facial expressions, yet the underlying nature of his deficit remains unknown. During typical face processing, normal sighted individuals extract information about exp...

The practice of combining digital and face-to-face elements into blended learning courses is becoming the new normal in higher education offers a promising format. While studies on effects have so far focused mostly online components blends, success also rests quality integrated activities. This scoping review examines evidence from 59 experimental conducted settings to explore what makes effic...

In this paper, there are two main topics to generate a 3D facial model from 2D face images. The first topic is to extract facial components such as eyebrows, eyes, nose, ear, mouth and face contour on the face images, and the second is to create 3D individualized face model using extracted facial components information at previous step. The generated final face model has an individualized shape...

BACKGROUND Some evidence suggests parents are drawn to media-based interventions over face-to-face interventions, but little is known about the factors associated with parents' use of Internet-based or Internet-enhanced programs, especially among military families. Research is needed to understand characteristics of parents who may be most likely to use online components or attend face-to-face ...

For face modeling, an And-Or graph model was first proposed in [9] as a compositional representation for high resolution face images. In an And-Or graph, the And nodes represent coarse-to-fine decompositions and the Or-nodes represent alternative components for diversity. The And-Or graph face model, as Fig.1 illustrates, has three levels: the first level describes the general appearance of glo...

In this paper, we propose a generation of feature image for face recognition. Feature image is generated using Discrete Cosine Transform (DCT), which tries to best classify different face images by maximizing the individual difference between face images. Low, Mid, and High frequency components of DCT are used to hold different information of face by providing a local description of different f...