Paper Details

Gesture is so natural way to communicate. Hand Gesture is invariably used in everyday life style .A novelmethod of dynamic hand gesture recognition based on Speeded Up Robust Features (SURF). Hand gesture recognitionmethod 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 InstructionCommunicate at a distance. This system consists of four stages: image acquisition, feature extraction, classification andrecognition. 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 toextract the feature of the input image based on SURF(speeded up robust method). Finally, a artificial neural network isuse to recognize the hand gestures. The performance of the system is tested on real time data. The proposed algorithm istested on Waving hand gestures and yields a satisfactory recognition rate which is 100% on the training set and 91.2%on the testing set.

Miss. Dimpal Korake, Prof. Vikas Marathe, “REAL TIME DYNAMIC HAND GESTURE RECOGNITION FOR HUMAN COMPUTER INTERACTION”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 5, Issue 1, pp. 670-677, January 2018.