Guilin Yao, Harbin Institute of Technology, Harbin, China
Hongxun Yao, Harbin Institute of Technology, Harbin, China
Xin Liu, Harbin Institute of Technology, Harbin, China
Feng Jiang, Harbin Institute of Technology, Harbin, China
Up to now, continuous sign language recognition is mainly based on statistical methods, especially Hidden Markov Models (HMM) and Viterbi-Beam searching. However, the recognition speed often gets unacceptable with an increased vocabulary, which could cause a long time delay that is not fit for the real time recognition system. To speed up the recognition process, we present a method using One-Pass (OP) pre-searching before Viterbi recognition. The experiments are processed in the large vocabulary database. Results show that the average recognition speed of OP/Viterbi approach can get a notable raise comparing with the single frame?s without reducing too much recognition accuracy.
Citation:
Guilin Yao, Hongxun Yao, Xin Liu, Feng Jiang, "Real Time Large Vocabulary Continuous Sign Language Recognition Based on OP/Viterbi Algorithm," icpr, vol. 3, pp.312-315, 18th International Conference on Pattern Recognition (ICPR'06) Volume 3, 2006