Online human activity recognition employing hierarchical hidden Markov models
Published 2019 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Online human activity recognition employing hierarchical hidden Markov models
Authors
Keywords
Online activity recognition, Streaming sensor data, Activity segmentation, Hierarchical hidden Markov models, Smart homes, Internet of things
Journal
Journal of Ambient Intelligence and Humanized Computing
Volume -, Issue -, Pages -
Publisher
Springer Science and Business Media LLC
Online
2019-07-09
DOI
10.1007/s12652-019-01380-5
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Temporal features and relations discovery of activities from sensor data
- (2018) Ehsan Nazerfard Journal of Ambient Intelligence and Humanized Computing
- A new approach based on temporal sub-windows for online sensor-based activity recognition
- (2018) Macarena Espinilla et al. Journal of Ambient Intelligence and Humanized Computing
- Activity Recognition in Sensor Data Streams for Active and Assisted Living Environments
- (2017) Fadi Al Machot et al. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
- Activity inference engine for real-time cognitive assistance in smart environments
- (2017) Jianguo Hao et al. Journal of Ambient Intelligence and Humanized Computing
- Learning movement patterns of the occupant in smart home environments: an unsupervised learning approach
- (2016) Tongda Zhang et al. Journal of Ambient Intelligence and Humanized Computing
- Towards improving feature extraction and classification for activity recognition on streaming data
- (2016) Nawel Yala et al. Journal of Ambient Intelligence and Humanized Computing
- Two-Layer Hidden Markov Model for Human Activity Recognition in Home Environments
- (2016) M. Humayun Kabir et al. International Journal of Distributed Sensor Networks
- Activity recognition with weighted frequent patterns mining in smart environments
- (2015) Jiahui Wen et al. EXPERT SYSTEMS WITH APPLICATIONS
- Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data
- (2015) Tobias Nef et al. SENSORS
- Dynamic sensor event segmentation for real-time activity recognition in a smart home context
- (2014) Jie Wan et al. Personal and Ubiquitous Computing
- Hierarchical activity recognition for dementia care using Markov Logic Network
- (2014) K. S. Gayathri et al. Personal and Ubiquitous Computing
- Clustering-Based Ensemble Learning for Activity Recognition in Smart Homes
- (2014) Anna Jurek et al. SENSORS
- Concurrent activation events based trajectory propagation in smart environments
- (2014) Tongda Zhang et al. Journal of Ambient Intelligence and Humanized Computing
- Segmenting sensor data for activity monitoring in smart environments
- (2012) Xin Hong et al. Personal and Ubiquitous Computing
- Dynamic sensor data segmentation for real-time knowledge-driven activity recognition
- (2012) George Okeyo et al. Pervasive and Mobile Computing
- Activity recognition on streaming sensor data
- (2012) Narayanan C. Krishnan et al. Pervasive and Mobile Computing
- Activity Discovery and Activity Recognition: A New Partnership
- (2012) Diane J. Cook et al. IEEE Transactions on Cybernetics
- Recognizing interleaved and concurrent activities using qualitative and quantitative temporal relationships
- (2011) Rim Helaoui et al. Pervasive and Mobile Computing
- Learning Setting-Generalized Activity Models for Smart Spaces
- (2010) Diane Cook IEEE INTELLIGENT SYSTEMS
- An activity monitoring system for elderly care using generative and discriminative models
- (2010) T. L. M. van Kasteren et al. Personal and Ubiquitous Computing
- Activity Recognition for the Smart Hospital
- (2008) D. Sanchez et al. IEEE INTELLIGENT SYSTEMS
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now