Integrated approach of skin-color detection and depth information for hand and face localization

Real-time hand and face localization is a challenging problem in many application scenarios such as face and gesture recognition in computer vision and robotics. This paper proposes a robust method which can locate multiple faces and hands simultaneously under the changing environment of light illumination and complex background in real time by using skin-color detection and K-means in conjunction with stereoscopic depth information. Skin-color detection in color image with elliptical boundary model to identify possible areas of human skin-color. The depth map captured from three-dimensional depth sensor Kinect is used to segment human body to remove the skin-color noise in the background and separate hands from face based on their positions. Then K-means algorithm clusters the detected skin-color pixels into three blobs to obtain the center points of hands and face. Experimental results demonstrate that the proposed method in localization of human hands and face is robust over various body postures and complex environmental circumstances in video sequences.