Ensemble Manifold Rank Preserving for Acceleration-Based Human Activity Recognition

CORC > 西安光学精密机械研究所 > 中国科学院西安光学精密机械研究所 > 光学影像学习与分析中心

	Ensemble Manifold Rank Preserving for Acceleration-Based Human Activity Recognition
	Tao, Dapeng 1; Jin, Lianwen 1; Yuan, Yuan2 ; Xue, Yang 1
刊名	ieee transactions on neural networks and learning systems
	2016-06
卷号	27 期号:6 页码:1392-1404
关键词	Frequency domain analysis Mobile devices Pattern recognition Ubiquitous computing
ISSN号	2162237x
产权排序	2
英文摘要	with the rapid development of mobile devices and pervasive computing technologies, acceleration;based human activity recognition, a difficult yet essential problem in mobile apps, has received intensive attention recently. different acceleration signals for representing different activities or even a same activity have different attributes, which causes troubles in normalizing the signals. we thus cannot directly compare these signals with each other, because they are embedded in a nonmetric space. therefore, we present a nonmetric scheme that retains discriminative and robust frequency domain information by developing a novel ensemble manifold rank preserving (emrp) algorithm. emrp simultaneously considers three aspects: 1) it encodes the local geometry using the ranking order information of intraclass samples distributed on local patches; 2) it keeps the discriminative information by maximizing the margin between samples of different classes; and 3) it finds the optimal linear combination of the alignment matrices to approximate the intrinsic manifold lied in the data. experiments are conducted on the south china university of technology naturalistic 3;d acceleration;based activity dataset and the naturalistic mobile;devices based human activity dataset to demonstrate the robustness and effectiveness of the new nonmetric scheme for acceleration;based human activity recognition. © 2012 ieee.
收录类别	EI
语种	英语
内容类型	期刊论文
源URL	[http://ir.opt.ac.cn/handle/181661/28253]
专题	西安光学精密机械研究所_光学影像学习与分析中心
作者单位	1.School of Electronic and Information Engineering, South China University of Technology, Guangzhou; 510641, China 2.Center for OPTical IMagery Analysis and Learning, State Key Laboratory of Transient Optics and Photonics, Xi'An Institute of Optics and Precision Mechanics, Xi'an; 710119, China
推荐引用方式 GB/T 7714	Tao, Dapeng,Jin, Lianwen,Yuan, Yuan,et al. Ensemble Manifold Rank Preserving for Acceleration-Based Human Activity Recognition[J]. ieee transactions on neural networks and learning systems,2016,27(6):1392-1404.
APA	Tao, Dapeng,Jin, Lianwen,Yuan, Yuan,&Xue, Yang.(2016).Ensemble Manifold Rank Preserving for Acceleration-Based Human Activity Recognition.ieee transactions on neural networks and learning systems,27(6),1392-1404.
MLA	Tao, Dapeng,et al."Ensemble Manifold Rank Preserving for Acceleration-Based Human Activity Recognition".ieee transactions on neural networks and learning systems 27.6(2016):1392-1404.