The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Discovery of activity patterns using topic models
Abstract
In this work we propose a novel method to recognize daily routines as a probabilistic combination of activity patterns. The use of topic models enables the automatic discovery of such patterns in a user's daily routine. We report experimental results that show the ability of the approach to model and recognize daily routines without user annotation.
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Cites
Fine-Grained Activity Recognition by Aggregating Abstract Object Usage
Patterson, D. J., Fox, D., Kautz, H., & Philipose, M. (2005) · Ninth IEEE International Symposium on Wearable Computers (ISWC'05) · doi:10.1109/iswc.2005.22 · Cited by 452
Layered representations for human activity recognition
Oliver, N., Horvitz, E., & Garg, A. (2003) · Proceedings. Fourth IEEE International Conference on Multimodal Interfaces · doi:10.1109/icmi.2002.1166960 · Cited by 312
Discovering Characteristic Actions from On-Body Sensor Data
Minnen, D., Starner, T., Essa, I., & Isbell, C. (2006) · 2006 10th IEEE International Symposium on Wearable Computers · doi:10.1109/iswc.2006.286337 · Cited by 132
Cited by
A tutorial on human activity recognition using body-worn inertial sensors
Bulling, A., Blanke, U., & Schiele, B. (2014) · ACM Computing Surveys · doi:10.1145/2499621 · Cited by 1,668
Self-citationCollecting complex activity datasets in highly rich networked sensor environments
Roggen, D., Calatroni, A., Rossi, M., Holleczek, T., Forster, K., Troster, G., Lukowicz, P., Bannach, D., Pirkl, G., Ferscha, A., et al. (2010) · 2010 Seventh International Conference on Networked Sensing Systems (INSS) · doi:10.1109/inss.2010.5573462 · Cited by 788
The Opportunity challenge: A benchmark database for on-body sensor-based activity recognition
Chavarriaga, R., Sagha, H., Calatroni, A., Digumarti, S. T., Tröster, G., Millán, J. D. R., & Roggen, D. (2013) · Pattern Recognition Letters · doi:10.1016/j.patrec.2012.12.014 · Cited by 742
Eye Movement Analysis for Activity Recognition Using Electrooculography
Bulling, A., Ward, J. A., Gellersen, H., & Tröster, G. (2011) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2010.86 · Cited by 718
Discovering important people and objects for egocentric video summarization
Lee, Y. J., Ghosh, J., & Grauman, K. (2012) · 2012 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2012.6247820 · Cited by 658
Metadata
- Authors
- Huynh, T., Fritz, M., & Schiele, B.
- Venue
- Proceedings of the 10th international conference on Ubiquitous computing
- Publisher
- ACM
- Published
- 2008-09-21
- Pages
- 10-19
- OpenAlex
- W2099336098
- Cited by
- 442
- References
- 3
- FWCI
- 19.77
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Huynh, T., Fritz, M., & Schiele, B. (2008). Discovery of activity patterns using topic models. Proceedings of the 10th international conference on Ubiquitous computing. https://doi.org/10.1145/1409635.1409638
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
