Predicting Behaviors of Residents by Modeling Preceding Action Transition from Trajectories
Taketoshi Mori, Shoji Tominaga, Hiroshi Noguchi,
Masamichi Shimosaka, Rui Fukui, and Tomomasa Sato
The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
-  B. Binmitt, B. Meyers, J. Krumm, A. Kern, and S. Shafer, “EasyLiving: Technologies for Intelligent Environments,” In Proc. of the 2nd Int. Symposium on Handheld and Ubiquitous Computing, pp. 12-29, 2000.
-  C. D. Kidd, R. J. Orr, G. D. Abowd, C. G. Atkeson, I. A. Essa, B. MacIntyre, E. Mynatt, T. E. Starner, and W. Newstetter, “The Aware Home: A Living Laboratory for Ubiquitous Computing Research,” In Proc. of the 2nd Int. Workshop on Cooperative Buildings, pp. 191-198, 1999.
-  J. H. Lee and H. Hashimoto, “Intelligent space,” In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, Vol.2, pp. 1358-1363, 2000.
-  T. Mori, H. Noguchi, A. Takada, and T. Sato, “Sensing Room: Distributed Sensor Environment for Measurement of Human Daily Behavior,” In 1st Int. Workshop on Networked Sensing Systems, pp. 40-43, 2004.
-  Y. Nakauchi, K. Noguchi, P. Somwong, T. Matsubara, and A. Namatame, “Vivid room: human intention detection and activity support environment for ubiquitous autonomy,” In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, Vol.1, pp. 773-778, 2003.
-  H. Noguchi, R. Urushibata, T. Sato, T. Mori, and T. Sato, “System for Tracking Human Position by Multiple Laser Range Finders Deployed in Existing Home Environment,” Aging Friendly Technology for Health and Independence, pp. 226-229, 2010.
-  T. Kanda, D. F. Glas, M. Shiomi, H. Ishiguro, and N. Hagita, “Who will be the customer?: A social robot that anticipates people’s behavior from their trajectories,” In Proc. of the 10th Int. Conf. on Ubiquitous Computing, pp. 380-389, 2008.
-  T. Sasaki, D. Brscic, and H. Hashimoto, “Human-Observation-Based Extraction of Path Patterns for Mobile Robot Navigation,” IEEE Trans. on Industrial Electronics, Vol.57, No.4, pp. 1401-1410, 2010.
-  B. D. Ziebart, N. Ratliff, G. Gallagher, C. Mertz, K. Peterson, J. A. Bagnell, M. Hebert, A. K. Dey, and S. Srinivasa, “Planning-based prediction for pedestrians,” Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 3931-3936, 2009.
-  M. Isard and A. Blake, “Condensation-Conditional density propagation for visual tracking,” Int. J. on Computer Vision, Vol.29, No.1, pp. 5-28, 1998.
-  T. Katoh, H. Arimura, and K. Hirata, “Mining Frequent Bipartite Episode from Event Sequences,” In Discovery Science, Lecture Notes in Computer Science, Vol.5808, pp. 136-151, Springer, 2009.
-  S. K. Harms and J. S. Deogun, “Sequential Association Rule Mining with Time Lags,” J. of Intelligent Information Systems, Vol.22, pp. 7-22, 2004.
-  J. Pei, J. Han, B. Mortazavi-Asl, H. Pinto, Q. Chen, U. Dayal, and M. Hsu, “PrefixSpan: Mining Sequential Patterns by Prefix-Projected Growth,” In Proc. of the 17th Int. Conf. on Data Engineering, pp. 215-224, 2001.
-  T. Uno, T. Asai, Y. Uchida, and H. Arimura, “An Efficient Algorithm for Enumerating Closed Patterns in Transaction Databases,” In Proc. of Discovery Science, pp. 16-31, 2004.
-  R. Srikant and R. Agrawal, “Mining Sequential Patterns: Generalizations and Performance Improvements,” In Proc. of the 5th Int. Conf. on Extending Database Technology: Advances in Database Technology, pp. 3-17, 1996.
-  H. Ohtani, T. Kida, T. Uno, and H. Arimura, “Efficient serial episode mining with minimal occurrences,” In Proc. of the 3rd Int. Conf. on Ubiquitous Information Management and Communication, pp. 457-464, 2009.
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