Entropy-based Markov chains for multisensor fusion

Journal of Intelligent and Robotic Systems: Theory and Applications

Volumn 29, Issue 2, 2000, Pages 161-189

  Chung, A C S ^a   Shen, H C ^a  

^a HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

DECISION THEORY; FUZZY SETS; MARKOV PROCESSES; POLYNOMIALS; PROBABILITY DISTRIBUTIONS; SENSOR DATA FUSION; UNCERTAIN SYSTEMS;

ENTROPY BASED MARKOV CHAIN; MEASUREMENT UNCERTAINTY; TRANSITION PROBABILITY;

ROBOTICS;

EID: 0034299907     PISSN: 09210296     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1008138126506     Document Type: Article

References (31)

1. Basir, O. A. and Shen, H. C.: Modelling and fusing uncertain multi-sensory data, J. Robotic Systems 13(2) (1996), 95-109.
2. Berger, J. O.: The robust Bayesian viewpoint, The International Library of Critical Writings in Econometrics 7: Bayesian Inference, Vol. 1, 1995, pp. 354-414.
3. Berler, A. and Shimony, S. E.: Bayes networks for sonar sensor fusion, in: Proc. of the 13th Conf. on Uncertainties in Artificial Intelligence, 1997, pp. 14-21.
4. Bloch, I. and Maitre, H.: Fusion of image information under imprecision, in: Aggregation and Fusion of Imperfect Information, 1998, pp. 189-213.
5. Buxton, H. and Gong, S. G.: Visual surveillance in a dynamic and uncertain world, Artificial Intelligence 78 (1995), 431-459.
6. Chung, A. C. S., Shen, H. C., and Basir, O. A.: A decentralized approach to sensory data integration, in: Proc. of 1997 IEEE/RSJ Internat. Conf. on Intelligent Robots and Systems, 1997, pp. 1409-1414.
7. Chung, A. C. S. and Shen, H. C.: Integrating dependent sensory data, in: Proc. of 1998 IEEE Internat. Conf. on Robotics and Automation, May 1998, pp. 3546-3552.
8. Clark, J. J. and Yuille, A. L.: Data Fusion for Sensory Information Processing Systems, Kluwer Academic, Dordrecht, 1990.
9. DeGroot, M. H.: Reaching a consensus, J. Amer. Statist. Assoc. 69(345) (1974), 118-121.
10. DeGroot, M. H.: Probability and Statistics, McGraw-Hill, New York, 1986.
11. Dromigny, A. and Zhu, Y. M.: Improving the dynamic range of real-time X-ray imaging systems via Bayesian fusion, J. Nondestructive Evaluation 16(3) (1997), 147-160.
12. Durrant-Whyte, H. F.: Sensor models and multisensor integration, Internat. J. Robotics Res. 7(6) (1988), 97-113.
13. Elfes, A.: Multi-source spatial data fusion using Bayesian reasoning integration, in: Data Fusion in Robotics and Machine Intelligence, Academic Press, New York, 1992, pp. 137-163.
14. Goodridge, S. G., Kay, M. G., and Luo, R. C.: Multilayered fuzzy behavior fusion for real-time reactive control of systems with multiple sensors, IEEE Trans. Industr. Electronics 43(3) (1996), 387-394.
15. Haddad, Z. S., Durden, S. L., and Im, E.: Bayesian fusion of trmm passive and active measurements, in: IGARSS'97, 1997 Internat. Geoscience and Remote Sensing Symposium, Remote Sensing - A Scientific Vision for Sustainable Development, Vol. 4, 1997, pp. 1642-1644.
16. Hall, D.: Mathematical Techniques in Multisensor Data Fusion, Artech Hourse, Boston, 1992.
17. Hillier, F. S. and Lieberman, G. J.: Introduction to Operations Research, McGraw-Hill, New York, 1990.
18. Huber, P. J.: Robust Statistics, Wiley, New York, 1981.
19. Hurn, M. A., Mardia, K. V., Hainsworth, T. J., Kirkbride, J., and Berry, E.: Bayesian fused classification of medical images, IEEE Trans. Medical Imaging 15(6) (1996), 850-858.
20. Kang, D. H., Luo, R. C., Hashimoto, H., and Harashima, F.: Position estimation for mobile robot using sensor fusion, in: Proc. of the 1994 Internat. Conf. on Multisensor Fusion and Integration for Intelligent Systems (MFI'94), October 1994, pp. 647-652.
21. Kittler, J., Matas, J., Jonsson, K., and Sanchez, M. U. R.: Combining evidence in personal identity verification systems, Pattern Recognition Lett. 18 (1997), 845-852.
22. Liu, J. and Chang, K. C.: Feature-based target recognition with a Bayesian network, Optical Engineering 35(3) (1996), 701-707.
23. Nadabar, S. G. and Jain, A. K.: Fusion of range and intensity images on a connection machine (cm-2), Pattern Recognition 28(1) (1995), 11-26.
24. Park, S. W. and Lee, C. S. G.: Fusion based sensor fault detection, in: Proc. of 1993 IEEE Internat. Sympos. on Intelligent Control, August 1993, pp. 156-161.
25. Press, W. H., Teukolsky, S. A., Vetterling, W. T., and Flannery, B. P.: Numerical Recipes in C: The Art of Scientific Computing, Cambridge Univ. Press, 1992.
26. Shannon, C. E.: A mathematical theory of communication, Bell Syst. Techn. J. 27 (1948), 379-423.
27. Solberg, A. H. S., Jain, A. K., and Taxt, T.: Multisource classification of remotely sensed data: Fusion of landsat tm and sar images, IEEE Trans. Geoscience Remote Sensing 32(4) (1994), 768-778.
28. Stassopoulou, A., Petrou, M., and Kittler, J.: Application of a bayesian network in a gis-based decision making system, Internat. J. Geographical Inform. Sci. 12(1) (1998), 23-45.
29. Stratton, D. A. and Stengel, R.: Real-time decision aiding: Aircraft guidance for wing shear avoidance, IEEE Trans. Aerospace Electronic Systems 31(1) (1995), 117-124.
30. Wallack, A. S. and Canny, J. F.: Generalized polyhedral object recognition and localization using crossbeam sensing, The Internat. J. Robotics Res. 16(4) (1997), 473-496.
31. Wolff, G. J.: Sensory fusion: Integrating visual and auditory information for recognizing speech, in: Proc. of the 1993 IEEE Internat. Conf. on Neural Networks, Vol. 2, 1993, pp. 672-677.