NDLI: Extreme learning machine-based device displacement free activity recognition model

Content Provider	Springer Nature Link
Author	Chen, Yiqiang Zhao, Zhongtang Wang, Shuangquan Chen, Zhenyu
Copyright Year	2012
Abstract	Activity recognition based on mobile device is an important aspect in developing human-centric pervasive applications like gaming, industrial maintenance and health monitoring. However, the data distribution of accelerometer is heavily affected by varying device locations and orientations, which will degrade the performance of recognition model. To solve this problem, we propose a fast, robust and device displacement free activity recognition model in this paper, which integrates principal component analysis (PCA) and extreme learning machine (ELM) to realize location-adaptive activity recognition. On the one hand, PCA is employed to reduce the dimensionality of feature space and extract robust features for recognition. On the other hand, in the online phase ELM is applied to classify the activity and adapt the recognition model to new device locations based on high confident recognition results in real time. Experimental results show that, with robust features and fast adaptation capability, the proposed model can adapt the classifier to new device locations quickly and obtain good recognition performance.
Starting Page	1617
Ending Page	1625
Page Count	9
File Format	PDF
ISSN	14327643
Journal	Soft Computing
Volume Number	16
Issue Number	9
e-ISSN	14337479
Language	English
Publisher	Springer-Verlag
Publisher Date	2012-02-07
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Extreme learning machine Activity recognition Principal component analysis Machine learning Computational Intelligence Mathematical Logic and Foundations Artificial Intelligence (incl. Robotics) Control, Robotics, Mechatronics
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Software Geometry and Topology

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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