Multiview Cauchy Estimator Feature Embedding for Depth and Inertial Sensor-Based Human Action Recognition.
Guo, Yanan; Tao, Dapeng; Liu, Weifeng; Cheng, Jun
刊名IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
2017
文献子类期刊论文
英文摘要The ever-growing popularity of Kinect and inertial sensors has prompted intensive research efforts on human action recognition. Since human actions were extracted from Kinect and inertial sensors, they can be characterized by multiple feature representations. By encoding the multiview features into a unified space, it could be optimal for human action recognition. In this paper, we propose a new unsupervised feature fusion method termed multiview Cauchy estimator feature embedding (MCEFE) for human action recognition. By minimizing empirical risk, MCEFE integrates the encoded complementary information in multiple views to find the unified data representation and the projection matrices. To enhance robustness to outliers, the Cauchy estimator is imposed on the reconstruction error. Furthermore, ensemble manifold regularization is enforced on the projection matrices to encode the correlations between different views and avoid overfitting. Experiments are conducted on the new Chinese Academy of Sciences-Yunnan University-multimodal human action database to demonstrate the effectiveness and robustness of MCEFE for human action recognition.
URL标识查看原文
语种英语
内容类型期刊论文
源URL[http://ir.siat.ac.cn:8080/handle/172644/11634]  
专题深圳先进技术研究院_集成所
作者单位IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
推荐引用方式
GB/T 7714
Guo, Yanan,Tao, Dapeng,Liu, Weifeng,et al. Multiview Cauchy Estimator Feature Embedding for Depth and Inertial Sensor-Based Human Action Recognition.[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2017.
APA Guo, Yanan,Tao, Dapeng,Liu, Weifeng,&Cheng, Jun.(2017).Multiview Cauchy Estimator Feature Embedding for Depth and Inertial Sensor-Based Human Action Recognition..IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS.
MLA Guo, Yanan,et al."Multiview Cauchy Estimator Feature Embedding for Depth and Inertial Sensor-Based Human Action Recognition.".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS (2017).
个性服务
查看访问统计
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

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。


©版权所有 ©2017 CSpace - Powered by CSpace