A Novel Sign Language Recognition Framework Using Hierarchical Grassmann Covariance Matrix

doi:10.1109/TMM.2019.2915032

CORC > 计算技术研究所 > 中国科学院计算技术研究所 > 中国科学院计算技术研究所期刊论文 > 英文

	A Novel Sign Language Recognition Framework Using Hierarchical Grassmann Covariance Matrix
	Wang, Hanjie 1,2; Chai, Xiujuan 1,2; Chen, Xilin 1,2
刊名	IEEE TRANSACTIONS ON MULTIMEDIA
	2019-11-01
卷号	21 期号:11 页码:2806-2814
关键词	Covariance matrices Hidden Markov models Manifolds Assistive technology Feature extraction Gesture recognition Correlation Sign language recognition grassmann covariance matrix grassmann manifold belief propagation sentence spotting
ISSN号	1520-9210
DOI	10.1109/TMM.2019.2915032
英文摘要	Visual sign language recognition is an interesting and challenging problem. To create a discriminative representation, a hierarchical Grassmann covariance matrix (HGCM) model is proposed for sign description. Furthermore, a multi-temporal belief propagation (MTBP) based segmentation approach is presented for continuous sequence spotting. Concretely speaking, a sign is represented by multiple covariance matrices, followed by evaluating and selecting their most significant singular vectors. These covariance matrices are transformed into a more compact and discriminative HGCM, which is formulated on the Grassmann manifold. Continuous sign sequences can be recognized frame by frame using the HGCM model, before being optimized by MTBP, which is a carefully designed graphic model. The proposed method is thoroughly evaluated on isolated and synthetic and real continuous sign datasets as well as on HDM05. Extensive experimental results convincingly show the effectiveness of our proposed framework.
资助项目	973 Program[2015CB351802] ; 973 Program[QYZDJ-SSW-JSC009]
WOS研究方向	Computer Science ; Telecommunications
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000494363000009
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/14833]
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Chai, Xiujuan
作者单位	1.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Wang, Hanjie,Chai, Xiujuan,Chen, Xilin. A Novel Sign Language Recognition Framework Using Hierarchical Grassmann Covariance Matrix[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2019,21(11):2806-2814.
APA	Wang, Hanjie,Chai, Xiujuan,&Chen, Xilin.(2019).A Novel Sign Language Recognition Framework Using Hierarchical Grassmann Covariance Matrix.IEEE TRANSACTIONS ON MULTIMEDIA,21(11),2806-2814.
MLA	Wang, Hanjie,et al."A Novel Sign Language Recognition Framework Using Hierarchical Grassmann Covariance Matrix".IEEE TRANSACTIONS ON MULTIMEDIA 21.11(2019):2806-2814.