Multi-Touch Gesture Recognition Based on Petri Net and Back Propagation Neural Networks
Wang De · 2010
To recognize gestures of multi-touch system,a framework including gesture description and recognition is proposed.Multi-touch gesture can be decomposed into atomic gestures and composite gestures.For gesture description,the back propagation neural networks(BPNN)is used to model the atomic gesture.Users' motions are mapped into composite gestures combined with atomic gestures logic,temporal and spatial relations.Petri nets(PN)introduced with logical,temporal,spatial descriptors are used to model the composite gesture.For recognition,BPNN is used as a classifier to recognize atomic gestures and the recognition results trigger the transition of Petri nets for composite gestures to realize the recognition.Experimental results show that the proposed method is robust to different users' customs and can recognize multi-touch gestures effectively.