Pedestrian-movement prediction based on mixed Markov-chain model

GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems

Volumn , Issue , 2011, Pages 25-33

  Asahara, Akinori ^a   Maruyama, Kishiko ^a   Sato, Akiko ^a   Seto, Kouichi ^a  

^a HITACHI LTD   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE MOBILE SERVICES; MARKOV-CHAIN MODELS; PEDESTRIAN MOVEMENT; PREDICTION ACCURACY; PREDICTION METHODS; PREDICTION RATE; SHOPPING MALL; TRACKING DATA; UNOBSERVABLE;

GEOGRAPHIC INFORMATION SYSTEMS; INFORMATION SYSTEMS; MARKOV PROCESSES; SHOPPING CENTERS;

FORECASTING;

EID: 84856412536     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2093973.2093979     Document Type: Conference Paper

References (22)

1. A. Asahara, A. Sato, and K. Maruyama. Evaluation of trajectory clustering based on information criteria for human activity analysis. IEEE International Conference on Mobile Data Management, pages 329-337, 2009.
2. Y. Asakura and E. Hato. Tracking survey for individual travel behaviour using mobile communication instruments. Transportation Research Part C: Emerging Technologies, 12(3-4):273-291, 2004. Intelligent Transport Systems: Emerging Technologies and Methods in Transportation and Traffic. (Pubitemid 39364223)
3. C. M. Bishop. Pattern Recognition and Machine Learning. Springer, New York, 2006.
4. D. Chudova, S. Gaffney, E. Mjolsness, and P. Smyth. Translation-invariant mixture models for curve clustering. In Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, pages 79-88, New York, NY, USA, 2003. ACM.
5. A. Daniel and S. Thad. Using gps to learn significant locations and predict movement across multiple users. In Personal and Ubiquitous Computing, volume 7, pages 275-286. Springer, 2003.
6. J. G. Dias and J. K. Vermunt. Latent class modeling of website user's search patterns: implications for online market segmentation. Journal of Retailing and Cosumer Services, 14:348-359, 2007.
7. A. D. V. Govea. Incremental Learning for Motion Prediction of Pedestrians and Vehicles. Springer-Verlag, 2010.
8. Hitachi Cable, Ltd. Launch of Hitachi AirLocation(TM), a Wireless LAN-Based Location Detection System Achieving Highly Accurate Positioning with Small Error Range of 1 to 3 Meters. http://www.hitachi-cable.co.jp/en/ infosystem/news/20031119la.html, 2003.
9. Hitachi, Ltd.. News release, 29 Sep. 2008 (in Japanese).
10. Hitachi Ltd. News release, 10 Feb 2010 (in Japanese). http://www.hitachi.co.jp/New/cnews/month/2010/02/0210.html, 2010.
11. J.-G. Lee, J. Han, and K.-Y. Whang. Trajectory clustering: a partition-and-group framework. In Proceedings of the 2007 ACM SIGMOD international conference on Management of data, pages 593-604, New York, NY, USA, 2007. ACM.
12. Loopt. Loopt®. http://www.loopt.com/.
13. D. Manandhar, S. Kawaguchi, M. Uchida, M. Ishii, and H. Tomohiro. IMES for mobile users, social implementation and experiments based on existing cellular phones for seamless positioning. Proc. of the Int. Symposium on GPS/GNSS 2008, Nov 2008.
14. Mckinsey Global Institute. Big data: The next frontier for innovation, competition and productivity. http://www.mckinsey.com/mgi/publications/big-data/ index.asp, 2011.
15. N. Meratnia and R. A. de By. Aggregation and comparison of trajectories. In Proceedings of the 10th ACM international symposium on Advances in geographic information systems, pages 49-54, New York, NY, USA, 2002. ACM.
16. O. Nuria, M., R. Barbara, and P. Alex, P. A bayesian computer vision system for modeling human interactions. In IEEE Transactions on Pattern Analysis and Machine Intelligence, volume 22, 2000.
17. C. S. Poulsen. Mixed markov and latent markov modelling applied to brand choice behaviour. Intern. Journal of Research in Marketing, 7:5-19, 1990.
18. Skyhook, Inc. Skyhook. http://www.skyhookwireless.com/.
19. T. Hamada, T. Hagiwara, T. Teramoto, S. Morishita, M. Umetsu, and M. Ohgama. A tree-dimensional pedestrian-flow simulation for high-rising buildings. In ACRI2008, volume LNCS 5191, pages 417-424. Springer, 2008.
20. G. Trajcevski, H. Ding, P. Scheuermann, R. Tamassia, and D. Vaccaro. Dynamics-aware similarity of moving objects trajectories. In Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems, pages 1-8, New York, NY, USA, 2007. ACM.
21. O. Woodman and R. Harle. Rf-based initialisation for inertial pedestrian tracking. In H. Tokuda, M. Beigl, A. Friday, A. Brush, and Y. Tobe, editors, Pervasive Computing, volume 5538 of Lecture Notes in Computer Science, pages 238-255. Springer Berlin/Heidelberg, 2009.
22. J. Yang, Y. Xu, and C. Chen. Human action learning via hidden markov model. Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, 27(1):34-44, Jan. 1997.