华中师范大学学报（自然科学版）2012，Vol.46Issue(5)：555-559,5.
基于HMM的手势识别研究
The study of gesture recognition based on hidden Markov model
摘要
Abstract
This paper designs a wearable gesture recognition system. Improved SWAB automatic endpoint detection algorithm is proposed in this paper. The K-means is employed to compute gesture vector quantization. Then the data as the input of hidden Markov model (HMM) is used to acquire the classification information. Experiments show that is an effective method for gesture recognition.关键词
手势识别/人机交互/端点检测/隐马尔可夫模型Key words
gesture recognition/ human-computer interaction/ endpoint detection/HMM分类
信息技术与安全科学引用本文复制引用
严焰,刘蓉,黄璐,陈婷..基于HMM的手势识别研究[J].华中师范大学学报（自然科学版）,2012,46(5):555-559,5.基金项目
华中师范大学中央高校基本科研业务费基金资助项目(CCNU10A02008) （CCNU10A02008）
教育部人文社会科学研究计划基金资助项目(10YJA870026). （10YJA870026）
