Authentication System Design Based on Dynamic Hand Gesture

Due to biometric immutability, an authentication system that depends on irrevocable biometric data (faces and fingerprints) is vulnerable to vicious attacks. Gestures, as short actions that contain static and dynamic behavioral information, are gradually replacing traditional biometrics. Compared to body gestures, hand gestures are more flexible and do not require the user’s entire body to appear in front of the camera. However, most existing feature extraction algorithms rely on the key point of a hand in motion or the image analysis of a static hand gesture, thereby making the authentication less real-time and less effective in the real-word. To alleviate these problems, we propose a user authentication system based on dynamic hand gestures jointly models the silhouette and skeletal properties of moving hands for user authentication. Our system obtains an average 0.105% false acceptance rate (FAR) and an average 3.40% false rejection rate (FRR) on the public Dynamic Hand Gesture 14/28 dataset.