Emotion Detection – Emota™ v2.0
The sample video demontrating software that detect emotional states in a realtime manner for mobile apps, desktop systems and interactive experiences.
This technique currently uses an pattern recogntion to identify shapes within a image field using Viola and Jones Open CV Haar-like features application [1], [2],[3] and a “feret” database [4] of facial image and support vector machine (LibSVM) [3] to classify the capture of the camera view field and identify if a face exists. The system processses the detected faces using an elastic bunch graph mapping technique
that is trained to determine facial expressions. These facial expressions are graphed on a sliding scale to match the distance from a target emotion graph, thus giving an approx-imate determination of the users mood.
Collaborators:
Pensyl, William Russell; Song Shuli Lily; Dias, Walson; Huang, Walter Yucheng Walter; Odell, Conor; Zhang, Yifan Henry