NDLI: Toward Personalized Activity Recognition Systems With a Semipopulation Approach

Content Provider	IEEE Xplore Digital Library
Author	Jin-Hyuk Hong Ramos, J. Dey, A.K.
Copyright Year	2013
Abstract	Activity recognition is a key component of context-aware computing to support people's physical activity, but conventional approaches often lack in their generalizability and scalability due to problems of diversity in how individuals perform activities, overfitting when building activity models, and collection of a large amount of labeled data from end users. To address these limitations, we propose a semipopulation-based approach that exploits activity models trained from other users; therefore, a new user does not need to provide a large volume of labeled activity data. Instead of relying on any additional information from users like their weight or height, our approach directly measures the fitness of others' models on a small amount of labeled data collected from the new user. With these shared activity models among users, we compose a hybrid model of Bayesian networks and support vector machines to accurately recognize the activity of the new user. On activity data collected from 28 people with a diversity in gender, age, weight, and height, our approach produced an average accuracy of 83.4% (kappa: 0.852), compared with individual and (standard) population models that had accuracies of 77.3% (kappa: 0.79) and 77.7% (kappa: 0.743), respectively. Through an analysis on the performance of our approach and users' demographic information, our approach outperforms others that rely on users' demographic information for recognizing their activities, which may contradict the commonly held belief that physically similar people would have similar activity patterns.
Starting Page	101
Ending Page	112
Page Count	12
File Size	775562
File Format	PDF
ISSN	21682291
Volume Number	46
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2016-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data models Sociology Statistics Training Calibration Support vector machines Robot sensing systems ubiquitous computing Pattern recognition sensor systems and applications
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Signal Processing Human Factors and Ergonomics Control and Systems Engineering Computer Networks and Communications Human-Computer Interaction Computer Science Applications

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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