A spatiotemporal data fusion model for occupancy state estimation: An evidential approach

Proceedings of the 11th International Conference on Information Fusion, FUSION 2008

Volumn , Issue , 2008, Pages

  Boudet, Laurence ^a   Midenet, Sophie ^a  

^a Gretia   (France)

Author keywords

Multi sensor fusion; Pedestrian crossing detection; Spatiotemporal data; Traffic sensors; Transferable belief model

Indexed keywords

CROSSINGS (PIPE AND CABLE); DATA FUSION; FOOTBRIDGES; FUSION REACTIONS; IMAGE CLASSIFICATION; INFORMATION FUSION; MODAL ANALYSIS; ROADS AND STREETS; SENSORS; STATE ESTIMATION; TRAFFIC SIGNALS;

MULTI-SENSOR FUSION; PEDESTRIAN CROSSING DETECTION; SPATIOTEMPORAL DATA; TRAFFIC SENSORS; TRANSFERABLE BELIEF MODEL;

SENSOR DATA FUSION;

EID: 56749148276     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIF.2008.4632365     Document Type: Conference Paper

References (10)

1. P. Smets and R. Kennes, "The Transferable Belief Model", Artificial Intelligence, vol. 66, pp. 191-243, 1994.
2. S. Midenet, F. Boillot and J.C. Pierrelée, "Signalized intersection with real-time adaptive control: on-field assessment of CO2 and pollutant emission prediction", Transportation Research D, vol. 9, pp. 29-47, 2004.
3. F. Boillot, S. Midenet and J.C. Pierrelée, "The real-time urban traffic control system CRONOS: algorithm and experiments", Transportation Research C, vol. 14, pp. 18-39, 2006.
4. \\www.citilog.com\index_en.php
5. D. Aubert, S. Bouzar, F. Lenoir and J.M. Blosseville, "Automic vehicle queue measurement at intersections using image-processing", in 8th International Conference on Road Traffic Monitoring and Control, vol. 422, pp. 100-104, 1996.
6. P. Smets, "Constructing the Pignistic Probability Function in a context of uncertainty", Uncertainy in Artificial Intelligence, vol. 5, pp. 29-39, 1990.
7. E. Ramosso, M. Rombaut and P. Pellerin, "A temporal belief filter improving human action recognition in videos", in International Conference on Acoustics, Speech and Signal Processing, Toulouse, France, 2006.
8. P. Smets and B. Ristic, "Kalman filter and joint tracking and classification based on belief functions in the TBM framework", Information Fusion, Special Issue on the Seventh International Conference on Information Fusion, Part II, vol. 8, no. 1, pp. 16-27, 2007.
9. D. Dubois and H. Prade, "Representation and combination of uncertainty with belief functions and possibility measures", Computational Intelligence, vol. 4, pp. 244-264, 1988.
10. R.R. Yager, "On the Dempster-Shafer framework and new combination rules", Information Sciences, vol. 41, pp. 93-137, 1987.