Facial recognition system introduced varying technologies to the procedure. Some of the most notable include the following techniques: Some face recognition algorithms identify facial features by extracting landmarks, or features, from an image of the subject's face. For example, an algorithm may analyze the relative position, size, and/or shape of the eyes, nose, cheekbones, and jaw. These features are then used to search for other images with matching features. Other algorithms normalize a gallery of face images and then compress the face data, only saving the data in the image that is useful for face recognition. A probe image is then compared with
Facial coding features of face (mouth, eyebrows etc.) and analyzes movement, shape and texture composition of these regions to identify facial action units. Therefore, it is possible to track tiny movements of facial muscles in individuals’ face and translate them into universal facial expressions that convey happiness, surprise, sadness, anger and others. An algorithm developed by EyeSee can detect the following seven emotions: happiness, surprise, puzzle, disgust, fear, sadness and neutral. The results of facial coding provide insight into viewers’ spontaneous, unfiltered reactions to visual content, by recording and automatically analyzing facial expressions during the process. It enables moment-by-moment emotional and cognitive