Face recognition software measures various parameters in a mug shot, such as the distance between the person's eyes, the height from lip to top of their nose and various other metrics and then compares it with photos of people in the database that have been tagged with a given name. Now, new research looks to take that one step further in recognizing the emotion portrayed by a face.
The first involves developing an algorithm that can precisely identify and define the features of the human face. The second then analyses the particular positions and shapes of the face. The third phase then associates those features with a person's emotional state to decide whether they are happy, sad, angry, surprised, fearful or disgusted. Preliminary tests gave a 94 percent success rate the team reports.
"Our experimental results suggest that the introduced method is able to support more accurate classification of emotion classification from images of faces," the team says. They add that additional refinements to the classification algorithms will improve their emotion detector still further.
Link:
http://www.sciencedaily.com/releases/2014/09/140916141535.htm
