Dynamic Gesture Recognition Using Hidden Markov Model in Static Background

Human Computer Interaction is a challenging endeavour. Being able to communicate with your computer (or robot) just as we humans interact with one another has been the prime objective of HCI research since the last two decades. A number of devices have been invented, each bringing with it a new aspect of interaction. Much work has gone into Speech and Gesture Recognition to develop an approach that would allow users to interact with their system by simple using their voice or simple intuitive gestures as against sitting in front of the computer and using a mouse or keyboard. Natural Interaction must be fast, convenient and reliable. In our project, we intend to develop one such natural interaction interface, one that can recognize hand gesture movements in real time using HMM but by using Computer Vision instead of sensory gloves.

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