Recognizing activities and spatial context using wearable sensors

Proceedings of the 22nd Conference on Uncertainty in Artificial Intelligence, UAI 2006

Volumn , Issue , 2006, Pages 494-502

  Subramanya, Amarnag ^a   Raj, Alvin ^a   Bilmes, Jeff ^a   Fox, Dieter ^a  

^a UNIVERSITY OF WASHINGTON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA ANNOTATION; DYNAMIC GRAPHICAL MODELS; HIGH FLEXIBILITY; LABELED DATA; PERFORMANCE GAIN; SIMULTANEOUS USE; SPATIAL CONTEXT; TRAINING DATA; WEARABLE SENSORS;

ARTIFICIAL INTELLIGENCE;

SENSORS;

EID: 80053177991     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (19)

1. D. Ashbrook and T. Starner. Using GPS to learn significant locations and predict movement across multiple users. Personal and Ubiquitous Computing, 7(5), 2003.
2. L. Bao and S Intille. Activity recognition from user-annotated acceleration data. In Proc. of the International Conference on Pervasive Computing and Communications, 2004.
3. J. Bilmes. On soft evidence in bayesian networks. Technical Report UWEETR-2004-0016, University of Washington, Dept. of EE, 2004.
4. J. Bilmes and C. Bartels. On triangulating dynamic graphical models. In Uncertainty in Artificial Intelligence: Proceedings of the Nineteenth Conference (UAI-2003), pages 47-56. Morgan Kaufmann Publishers, 2003.
5. A. Blum and T. Mitchell. Combining labeled and unlabeled data with co-training. In COLT: Proceedings of the Workshop on Computational Learning Theory, 1998.
6. O. Chapelle, A. Zien, and B. Schölkopf, editors. Semi-supervised learning. MIT Press, 2006.
7. T. Dean and K. Kanazawa. Probabilistic temporal reasoning. In Proc. of the National Conference on Artificial Intelligence (AAAI), 1988.
8. R. Dechter. Constraint Processing. Morgan Kaufmann, 2003.
9. J. Ho and S. Intille. Using context-aware computing to reduce the perceived burden of interruptions from mobile devices. In Proc. of the Conference on Human Factors in Computing Systems (CHI), 2005.
10. N. Kern, B. Schiele, H. Junker, P. Lukowicz, and G. Trster. Wearable sensing to annotate meeting recordings. In In The 6th International Symposium on Wearable Computers (ISWC), 2002.
11. N. Kern, B. Schiele, and A. Schmidt. Recognizing context for annotating a live life recording. Personal and Ubiquituous Computingd, 2005.
12. J. Lester, T. Choudhury, N. Kern, G. Borriello, and B. Hannaford. A hybrid discriminative-generative approach for modeling human activities. In Proc. of the International Joint Conference on Artificial Intelligence (IJCAI), 2005.
13. L. Liao, D. Fox, and H. Kautz. Learning and inferring transportation routines. In Proc. of the National Conference on Artificial Intelligence (AAAI), 2004.
14. L. Liao, D. Fox, and H. Kautz. Location-based activity recognition. In Advances in Neural Information Processing Systems (NIPS), 2005.
15. P. Lukowicz, J. Ward, H. Junker, M. Stäger, G. Tröster, A. Atrash, and T. Starner. Recognizing workshop activity using body worn microphones and accelerometers. In Proc. of Pervasive Computing, 2004.
16. D. Patterson, L. Liao, K. Gajos, M. Collier, N. Livic, K. Olson, S. Wang, D. Fox, and H. Kautz. Opportunity Knocks: a system to provide cognitive assistance with transportation services. In International Conference on Ubiquitous Computing (UbiComp), 2004.
17. J. Pearl. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann Publishers, Inc., 1988.
18. A. Raj, A. Subramanya, J. Bilmes, and D. Fox. Rao-Blackwellized particle filters for recognizing activities and spatial context from wearable sensors. In Experimental Robotics: The 10th International Symposium, Springer Tracts in Advanced Robotics (STAR). Springer Verlag, 2006.
19. D. Yarowsky. Unsupervised word sense disambiguation rivaling supervised methods. In Proceedings of the 33rd Annual Meeting of the Association for Computational Linguistics, 1995.