Multi-posture fingertip tracking method for natural man-machine interaction

The present invention discloses a multi-posture fingertip tracking method for natural man-machine interaction. The method comprises the following steps: S1: acquiring RGBD data by adopting Kinect2, including depth information and color information; S2: detecting a hand region: by means of conversion of a color space, converting a color into a space that does not obviously react to brightness so as to detect a complexion region, then detecting a human face by means of a human face detection algorithm, so as to exclude the human face region and obtain the hand region, and calculating a central point of a hand; S3: by means of the depth information and in combination with an HOG feature and an SVM classifier, identifying and detecting a specific gesture; and S4: by means of positions of preceding frames of fingertips and in combination with an identified region of the hand, performing prediction on a current tracking window, and then detecting and tracking a fingertip by means of two modes, i.e. a depth-based fingertip detection mode and a form-based fingertip detection mode. The method disclosed by the present invention is mainly used for performing detection and tracking on a single fingertip under motion and various postures, and relatively high precision and real-time property need to be ensured.