摘要
选取Cyberglove型号数据手套作为手语输入设备 ,采用DGMM (DynamicGaus sianMixtureModel)作为手势词识别技术 ,提出了基于相对熵的搜索策略 ,并将其应用于基于半连续DGMM的手势词识别中以提高手势词识别速度。实验结果表明 ,采用搜索策略后手势词识别效果与原来相当 ,而识别速度提高了近 1 5倍。
Considering the speed and performance of the recognition system, Cyberglove is selected as gesture input device in author's sign language recognition system, Semi continuous Dynamic Gaussian Mixture Model (SCDGMM) is used as recognition technique, and a search scheme based on relative entropy is proposed and is applied to SCDGMM based sign word recognition. Comparing with SCDGMM recognizer without searching scheme, the recognition time of SCDGMM recognizer with searching scheme reduces almost 15 times.
出处
《高技术通讯》
EI
CAS
CSCD
2001年第6期23-27,共5页
Chinese High Technology Letters
基金
863计划 ( 863 3 0 6 ZT0 3 0 1 2 )
国家自然科学基金 ( 697893 0 1)
国家教委跨世纪人才基金
中国科学院百人计划资助项目
