Local descriptors are the most effective textural image recognition methods. Local
descriptors generally consist of two phases. These are binary feature coding and histogram …

Visual detections of face expression have become much difficult job and yields in reduced
preciseness against the automated face expression identification making use of image …

Nowadays, many researches are being carried out in the field of 3D object recognition. All
developed 3D recognition approaches are based on 2D data processing (images) or 3D …

Facial landmarks represent regions of interest whose detection and localization generate
features supporting the identification of movements, feelings, and reactions. Most facial …

Facial expression recognition (FER) has become an increasingly important research topic
due toits various applications in such fields as human-computer interaction, psychology, and …

The major challenges, which come across face recognition system, are to find the age and
gender in 2D/3D image of the person specifically in cloud environment. This paperis …

Moreover, we also combine both descriptors in order to improve the system efficiency. For
the classification part of the system, we choose to use the multi-class Support Vector …

In general, the recognition involves several steps as follows: data acquisition, pre-
processing, segmentation, feature extraction and classification. Automatic facial expression …

Capturing non-verbal information from a face is the most important phase in emotion
recognition through facial expression. In order to do that, it needs to find suitable features …

En la actualidad el uso del reconocimiento de emociones en sistemas de visión se ha
incrementado debido a su utilidad en diversas áreas. Las emociones son reflejadas en el …