HAND GESTURE RECOGNITION FOR HUMAN COMPUTER INTERACTION: A REVIEW

In today's computer age, difficult to manually compare live image with trained database images so it is very necessary to perform all this manual work by computers. In the recent years new technologies of Human Computer Interaction (HCI) are being developed to deliver user's command to robots. The objective of this paper is to compare all various algorithms invited for gesture detection and recognition such as support vector machine, neural networks, and adaptive boosting (AdaBoost).Among these methods, AdaBoost based handpose detectors are trained with a reduced Haar-like feature set to make the detector robust.