Abstract
When a person enters a room, he or she immediately develops a mental concept about “what is going on” in the room; for example, people may be working in the room, people may be engaged in a conversation, or the room may be empty. The CHIL services depend on just the same kind of semantic description, which is termed activity in the following. The “Connector” or the “Memory Jog”, for example, could provide support that is appropriate for the given context if it knew about the current activity at the user’s place. This kind of higher-level understanding of human interaction processes could then be used, e.g., for rating the user’s current availability in a certain situation.
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References
A. F. Bobick and J. W. Davis. The recognition of human movement using temporal templates. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(3):257–267, 2001.
G. Bradski and J. Davis. Motion segmentation and pose recognition with motion history gradients. Machine Vision and Applications, 13(3):174–184, 2002.
C. Canton-Ferrer, J. R. Casas, and M. Pardàs Human model and motion based 3D action recognition in multiple view scenarios (invited paper). In 14th European Signal Processing Conference, EUSIPCO, University of Pisa, Florence, Italy, 4–9 Sept. 2006.
S. Dockstader, M. Berg, and A. Tekalp. Stochastic kinematic modeling and feature extraction for gait analysis. IEEE Transactions on Image Processing, 12(8):962–976, 2003.
M. Hu. Visual pattern recognition by moment invariants. IEEE Transactions on Information Theory, 8(2):179–187, 1962.
Y. A. Ivanov and A. F. Bobick. Recognition of visual activities and interactions by stochastic parsing. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22:852–872, 2000.
J. L. Landabaso and M. Pardas. Foreground regions extraction and characterization towards real-time object tracking. In Machine Learning for Multimodal Interaction (MLMI), LNCS 3869, pages 241–249. Springer, 2006.
K. Lari and S. Young. The estimation of stochastic context-free grammars using the inside-outside algorithm. Computer, Speech and Language, 4:35–56, 1990.
C. Lo and H. Don. 3-D oment forms: Their construction and application to object identification and positioning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11(10):1053–1064, 1989.
N. M. Oliver, B. Rosario, and A. Pentland. A Bayesian computer vision system for modeling human interactions. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(8):831–843, 2000.
R. Rosales. Recognition of human action using moment-based features. Boston University Computer Science Technical Report, BU, pages 98–120, 1998.
C. Stauffer and W. E. L. Grimson. Learning patterns of activity using real-time tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(8):747–757, 2000.
C. Wojek, K. Nickel, and R. Stiefelhagen. Activity recognition and room level tracking in an office environment. In IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, Heidelberg, Germany, Sept. 2006.
D. H. Younger. Recognition and parsing of context-free languages in time n3. Information and Control, 10:189–208, 1967.
D. Zhang, D. Gatica-Perez, S. Bengio, and I. McCowan. Semi-supervised adapted HMMs for unusual event detection. In Computer Vision and Pattern Recognition, pages 611–618, 2005.
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Nickel, K., Pardàs, M., Stiefelhagen, R., Canton, C., Landabaso, J.L., Casas, J.R. (2009). Activity Classification. In: Waibel, A., Stiefelhagen, R. (eds) Computers in the Human Interaction Loop. Human–Computer Interaction Series. Springer, London. https://doi.org/10.1007/978-1-84882-054-8_11
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DOI: https://doi.org/10.1007/978-1-84882-054-8_11
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