In this paper we present a biometric technique based on hand gestures. By means of the Microsoft Kinect sensor, the user’s hand is tracked while following a circle moving on the screen. Both 3D data about the position of the hand and 2D data about the position of the screen pointer are provided to different classifiers (SVM, Naive Bayes, Classification Tree, KNN, Random Forest and Neural Networks). Experiments carried out with 20 testers have demonstrated that the method is very promising for both identification and verification (with success rates above 90%), and can be a viable biometric solution, especially for soft biometric applications.
A Hand Gesture Approach to Biometrics
NUGRAHANINGSIH, NAHUMI;PORTA, MARCO;
2015-01-01
Abstract
In this paper we present a biometric technique based on hand gestures. By means of the Microsoft Kinect sensor, the user’s hand is tracked while following a circle moving on the screen. Both 3D data about the position of the hand and 2D data about the position of the screen pointer are provided to different classifiers (SVM, Naive Bayes, Classification Tree, KNN, Random Forest and Neural Networks). Experiments carried out with 20 testers have demonstrated that the method is very promising for both identification and verification (with success rates above 90%), and can be a viable biometric solution, especially for soft biometric applications.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
