Gesture Extraction using Depth Information

Gesture recognition has been a subject of much study lately as a promising technology for man-machine communication. Various methods have been proposed to locate and track body parts (e.g., hands and arms) including markers, colors, and gloves. In this paper, we have proposed a low cost, efficient hand gesture extraction technique that extracts gesture based on skin-colour segmentation followed by depth segmentation. In an ideal situation when human communicates with the computer using gesture, the depth of the gesture information and the other body parts differs; this information can be used to separate gesture from other complex background.