REAL TIME DYNAMIC HAND GESTURE RECOGNITION FOR HUMAN COMPUTER INTERACTION

Abstract

Gesture is so natural way to communicate. Hand Gesture is invariably used in everyday life style .A novel
method of dynamic hand gesture recognition based on Speeded Up Robust Features (SURF). Hand gesture recognition
method is widely used in the application area of Controlling mouse and/or keyboard functionality, mechanical system,
3D World, Manipulate virtual objects, Navigate in a Virtual Environment, Human/Robot Manipulation and Instruction
Communicate at a distance. This system consists of four stages: image acquisition, feature extraction, classification and
recognition. In the first stage input video of hand gestures are acquiesced by digital camera in approximate frame rate.
In second stage a rotation, translation, scaling and orientation invariant feature extraction method will be introduce to
extract the feature of the input image based on SURF(speeded up robust method). Finally, a artificial neural network is
use to recognize the hand gestures. The performance of the system is tested on real time data. The proposed algorithm is
tested on Waving hand gestures and yields a satisfactory recognition rate which is 100% on the training set and 91.2%
on the testing set.