PART AND STATE DETECTION FOR GESTURE RECOGNITION

Part and state detection for gesture recognition is useful for human-computer interaction, computer gaming, and other applications where gestures are recognized in real time. In various embodiments a decision forest classifier is used to label image elements of an input image with both part and state labels where part labels identify components of a deformable object, such as finger tips, palm, wrist, lips, laptop lid and where state labels identify configurations of a deformable object such as open, closed, up, down, spread, clenched. In various embodiments the part labels are used to calculate a center of mass of the body parts and the part labels, centers of mass and state labels are used to recognize gestures in real time or near real-time.