Sign language recognition based on HMM/ANN/DP
In this paper, a system designed for helping the deaf to communicate with others is presented. Some useful new ideas are proposed in design and implementation. An algorithm based on geometrical analysis for the purpose of extracting invariant feature to signer position is presented. Rn ANN-DP combined approach is employed for segmenting subwords automatically from the data stream of sign signals. To tackle the epenthesis movement problem, a DP-based method has been used to obtain the context-dependent models. Some techniques for system implementation are also given, including fast matching, frame prediction and search algorithms. The implemented system is able to recognize continuous large vocabulary Chinese Sign Language. Experiments show that proposed techniques in this paper are efficient on either recognition speed or recognition performance.
sign language recognition hand gesture recognition artificial neural network dynamic programming multimodal user interface virtual reality