ANN-Based Hand Gesture Recognition Using Self co-articulated Set of Features

ABSTRACT

Hand gesture recognition system can be a particularly challenging task because of the presence of several spatio-temporal variations like hand trembling, self co-articulation within a gesture, etc. during the segmentation stage. In this paper, we focus our attention on self co-articulation problem which has not been addressed before. With the addition of a new feature, i.e. removing the hand movement during pause state along with the velocity features within the gestures, we were able to perform the gesture spotting more smoothly for the isolated gestures. Moreover, a new set of novel features was added in the feature extraction stage: (1) number of self co-articulated stroke; (2) orientation of the self co-articulated strokes; (3) position of the hand; (4) distance between the start and end points of a gesture; and (5) ratio between the longest and shortest distances from centre. These features were fed to neural network classifier. The results of experimentation were carried out with 40 gestures and it showed an average true positive rate of 91.25%.

Keywords:

• Artificial Neural Network
• Feature extraction
• Gesture spotting
• Hand gesture recognition
• Human–computer interaction
• Self co-articulation

ACKNOWLEDGEMENTS

The authors acknowledge the Speech and Image Processing Laboratory under Department of ECE at National Institute of Technology, Silchar, India, for providing all necessary facilities to carry out the research work.

Additional information

Notes on contributors

Joyeeta Singha

Joyeeta Singha received her MTech degree in 2013 from Assam Don Bosco University and BE degree from GIMT, Guwahati, in 2011. She is currently pursuing PhD degree in the Department of Electronics and Communication Engineering at National Institute of Technology, Silchar. Her research interests include Image processing, hand gesture recognition, etc.

E-mail: [email protected]

Rabul Hussain Laskar

Rabul Hussain Laskar has completed his PhD degree from National Institute of Technology, Silchar, India, and his MTech from Indian Institute of Technology, Guwahati. He is currently working as head and assistant professor in the Department of Electronics and Communication Engineering at NIT, Silchar. His major research interests are in speech processing, image processing, digital signal processing, etc.

E-mail: [email protected]