An enhanced model for effective recognition and segmentation of SLG in dynamic video sequence using boosted learning algorithm

This paper proposes a new approach to solve the problem of real-time vision-based hand gesture recognition with the combination of hand posture and hand gesture analyses. The main objective of this is to divide the recognition problem into two levels according to the hierarchical property of hand gestures. This approach implements the posture detection with a statistical method based on Haar-like features and the dynamic approach for recognizing hand gestures using AdaBoost learning algorithm. With this proposed method, a group of hand postures is detected in dynamic video sequence with high recognition accuracy using boosted learning algorithm.