Hand & Upper Body Based Hybrid Gesture Recognition

Communication in today’s world is performed through the vocal sounds and body language. Vocal sounds are main tool for interaction, where body language and facial expressions also have important support. Even in few cases, interacting with physical world by using expressive movements like gestures and postures is much easier. In this paper, an approach is designed for Upper Body Pose Recognition and Hand Gesture Classification. This approach focuses on vision based technique. 6 classes of poses and 6 gesture classes are recognized during the testing process of this approach and neural network is used for classification. Keywords— Singular Value Decomposition (SVD), Principal Component Analysis (PCA), Artificial Neural Network (ANN), Pose Recognition, Hand Gesture Recognition.