Visual sign language recognition based on HMMs and Auto-regressive HMMs
文献类型：期刊论文
| 作者 | Yang, XL; Jiang, F; Liu, H; Yao, HX; Gao, W; Wang, CL |
| 刊名 | GESTURE IN HUMAN-COMPUTER INTERACTION AND SIMULATION
 |
| 出版日期 | 2006 |
| 卷号 | 3881页码:80-83 |
| 关键词 | computer vision sign language recognition HMM Auto-regressive HMM |
| ISSN号 | 0302-9743 |
| 英文摘要 | A sign language recognition system based on Hidden Markov Models(HMMs) and Auto-regressive Hidden Markov Models(ARHMMs) has been proposed in this paper. ARHMMs fully consider the observation relationship and are helpful to discriminate signs which don't have obvious state transitions while similar in motion trajectory. ARHMM which models the observation by mixture conditional linear Gaussian is proposed for sign language recognition. The corresponding training and recognition algorithms for ARHMM are also developed. A hybrid structure to combine ARHMMs with HMMs based on the trick of using an ambiguous word set is presented and the advantages of both models are revealed in such a frame work. |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000237042600009 |
| 出版者 | SPRINGER-VERLAG BERLIN |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/10735]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Yang, XL |
| 作者单位 | 1.Harbin Inst Technol, Dept Comp Sci, Harbin 15001, Peoples R China 2.Univ Illinois, Dept Comp Sci, Champaign, IL 61820 USA 3.Chinese Acad Sci, Inst Comp Technol, Beijing 100080, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yang, XL,Jiang, F,Liu, H,et al. Visual sign language recognition based on HMMs and Auto-regressive HMMs[J]. GESTURE IN HUMAN-COMPUTER INTERACTION AND SIMULATION,2006,3881:80-83. |
| APA | Yang, XL,Jiang, F,Liu, H,Yao, HX,Gao, W,&Wang, CL.(2006).Visual sign language recognition based on HMMs and Auto-regressive HMMs.GESTURE IN HUMAN-COMPUTER INTERACTION AND SIMULATION,3881,80-83. |
| MLA | Yang, XL,et al."Visual sign language recognition based on HMMs and Auto-regressive HMMs".GESTURE IN HUMAN-COMPUTER INTERACTION AND SIMULATION 3881(2006):80-83. |
入库方式： OAI收割
来源：计算技术研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。