The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Human Activity Recognition and Pattern Discovery
Open accessAbstract
In principle, activity recognition can be exploited to great societal benefits, especially in real-life, human centric applications such as elder care and healthcare. This article focused on recognizing simple human activities. Recognizing complex activities remains a challenging and active area of research and the nature of human activities poses different challenges. Human activity understanding encompasses activity recognition and activity pattern discovery. The first focuses on accurate detection of human activities based on a predefined activity model. An activity pattern discovery researcher builds a pervasive system first and then analyzes the sensor data to discover activity patterns.
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Cites
Introduction to Statistical Relational Learning
(2007) · doi:10.7551/mitpress/7432.001.0001 · Cited by 1,643
Research works printed but not linked: 7
- 10.1109/BSN.2006.6 · DOI · Paper page
- munguia-tapia, 2004, Activity Recognition in the Home Using Simple and Ubiquitous Sensors, Proc 2nd Int'l Conf Pervasive Computing (Pervasive 04), 158
- ogale, 2005, View-Invariant Modeling and Recognition of Human Actions Using Grammars, Proc Int'l Workshop Dynamical Vision, 115
- 10.1145/1409635.1409638 · DOI · Paper page
- helal, 2009, The Sensory Dataset Description Language
- intille, 2008, The NSF CRI CRD Development of Longitudinal Home Activity Datasets as a Shared Resource
- gu, 2009, epSICAR: An Emerging Patterns Based Approach to Sequential, Interleaved and Concurrent Activity Recognition, Proc IEEE 7th Ann Int'l Conf Pervasive Computing and Comm (PerCom 09), 1
Cited by
A Survey on Human Activity Recognition using Wearable Sensors
Lara, O. D., & Labrador, M. A. (2013) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2012.110112.00192 · Cited by 2,662
Multi-sensor fusion in body sensor networks: State-of-the-art and research challenges
Gravina, R., Alinia, P., Ghasemzadeh, H., & Fortino, G. (2017) · Information Fusion · doi:10.1016/j.inffus.2016.09.005 · Cited by 899
Transition-Aware Human Activity Recognition Using Smartphones
Reyes-Ortiz, J.-L., Oneto, L., Samà, A., Parra, X., & Anguita, D. (2016) · Neurocomputing · doi:10.1016/j.neucom.2015.07.085 · Cited by 740
Activity recognition on streaming sensor data
Krishnan, N. C., & Cook, D. J. (2014) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2012.07.003 · Cited by 488
Self-citationTransfer learning for activity recognition: a survey
Cook, D., Feuz, K. D., & Krishnan, N. C. (2013) · Knowledge and Information Systems · doi:10.1007/s10115-013-0665-3 · Cited by 447
Self-citation
Metadata
- Authors
- Kim, E., Helal, S., & Cook, D.
- Venue
- IEEE Pervasive Computing
- Published
- 2010-01
- Volume
- 9
- Issue
- 1
- Pages
- 48-53
- ISSN
- 1536-1268 (ISSN-L)
- OpenAlex
- W2103388129
- Cited by
- 704
- References
- 1
- FWCI
- 47.54
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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