PREDICTION of INDIVIDUAL'S MOVEMENT BASED on INTERESTING PLACES

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences

Volumn 1, Issue , 2012, Pages 31-36

  Feuerhake, U ^a  

^a LEIBNIZ UNIVERSITY HANNOVER   (Germany)

Author keywords

Algorithms; Analysis; Development; Modelling; Pattern; Prediction

Indexed keywords

EID: 84904871698     PISSN: 21949042     EISSN: 21949050     Source Type: Conference Proceeding    
DOI: 10.5194/isprsannals-I-2-31-2012     Document Type: Conference Paper

References (8)

1. Akinori Asahara, Kishiko Maruyama, Akiko Sato, and Kouichi Seto. 2011, Pedestrian-movement prediction based on mixed Markov-chain model. In Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS '11). ACM, New York, NY, USA, 25-33.
2. Ashbrook, D. and Starner, T., 2003, Using GPS to learn significant locations and predict movement across multiple users, Personal & Ubiquitous Computing 7: 275-286.
3. Baiget, P., Sommerlade, E., Reid, I., and Gonzàlez, J., 2008, Finding prototypes to estimate trajectory development in outdoor scenarios. In Proceedings of the First International Workshop on Tracking Humans for the Evaluation of their Motion in Image Sequences (THEMIS2008), September
4. Buchin, K, M. Buchin, M. van Kreveld, J. Luo, 2011, Finding long and similar parts of trajectories, Computational Geometry, Volume 44, Issue 9, November 2011, Pages 465-476.
5. Feuerhake, U., Kuntzsch, C., and Sester M., 2011, Finding interesting places and characteristic patterns in spatiotemporal trajectories, 8th LBS Symposium 2011, Vienna.
6. Helbing, D. and Molnár P., 1995, Social force model for pedestrian dynamics Physical Review E, 51 (5) (1995), pp. 4282-4286
7. Makris, D. and Ellis, T., 2002, Spatial and probabilistic modeling of pedestrian behavior, in Proc. Brit. Machine Vision Conf., vol. 2, Cardiff, U.K., pp. 557-566.
8. Schmid, F., Richter, K.-F., and Laube, P., 2009, Semantic Trajectory Compression, in Proceedings of Advances in Spatial and Temporal Databases, 11th International Symposium, SSTD 2009, Aalborg, Denmark, July 8-10, pp. 411-416.