Abstract
This paper reviews some knowledge representation approaches devoted to the sensor fusion problem, as encountered whenever images, signals, text must be combined to provide the input to a controller or to an inference procedure. The basic steps involved in the derivation of the knowledge representation scheme, are:
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(A)
locate a representation, based on exogeneous context information
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(B)
compare two representations to find out if they refer to the same object/entity
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(C)
merge sensor-based features from the various representations of the same object into a new set of features or attributes,
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(D)
aggregate the representations into a joint fused representation, usually more abstract than each of the sensor-related representations.
The importance of sensor fusion stems first from the fact that it is generally correct to assume that improvements in control law simplicity and robustness, as well as better classification results, can be achieved by combining diverse information sources. The second element, is that, e.g., spatially distributed sensing, or otherwise diverse sensing, does indeed require fusion as well.
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References
Kanode, T., Recovery of 3-D shape of an object from a single view, T.R. CMU-CS-79-153, Carnegie Mellon Univ. (1979).
MilgramD. L., Region extraction using convergent evidence, Computer Graphics and Image Processing, 2, 1–12 (1979).
Davis, L. S. and Rozenfeld, A., Cooperating processes for low level vision: a survey, T.R.-851, Univ. Maryland, Jan. 1980.
FuK. S., Syntactic Pattern Recognition, Academic Press, New York (1974).
Samet, H. and Rozenfeld, A., Quadtree structures for region processing, AD-A-077568, Nov. 1979.
Winston, P. H., Learning Structural Descriptions from Examples, The Psychology of Computer Vision, McGraw-Hill, Ch. 5 (1975).
MitchieA. and AggarwalJ. K., Multiple sensor integration/fusion through image processing, J. Optical Engineering, 25, 380–386 (1986).
Keown, D. M., Knowledge structuring in task oriented image databases, Proc. IEEE Workshop on Picture Data Processing, Description and Management, Aug. 1980, pp. 145–151 (1980).
FuK. S. and YuT. S., Statistical Pattern Classification Using Contextual Information, Wiley, New York (1980).
Wright, F. L., Fusion of multisensor data, Signal, Oct. 1980, pp. 39–43.
KohonenT., Associative Memory, Springer, New York (1978).
Pau, L. F., An Introduction to Infrared Image Acquisition and Recognition, Wiley/RSP (1985).
Besl, P. and Jain, R., Range image understanding, Proc. IEEE Conf. Computer Vision and Pattern Recognition, p. 430 (1985).
Mitchie, A., On combining stereopsis and kineopsis for space perception, Proc. 1st IEEE Conf. Artifical Intelligence Applications, p. 156 (1984).
Gil, B., Mitchie, A., and Aggarwal, J. K., Experiments in combining range and intensity edge maps. Comp. Graph. Image Proc., Vol. 21, p. 395 (1983).
Benda, M., Jagannathan, V., and Dodhiawala, R., On optimal cooperation of knowledge sources, T.R. Boeing A.I. Center, Boeing Computer Services (1985).
Drazovich, R. J., Sensor fusion in tactical warfare, AIAA paper No. 83-2398, American Institute of Aeronautics and Space (1983).
Forman, A. V., Rowland, P. J., and Pemberton, W. G., Contextual analysis of tactical scenes, in Applications of Artificial Intelligence, Proc. SPIE, Vol. 485, p. 189, p. 198 (1984).
Garvey, T. D., Lowrance, J. D., and Fischler, M. A., An inference technique or integrating knowledge from disparate sources, Proc. 1981 Int. J. Conference on Artificial Intelligence, p. 319 (1981).
LambirdB. A., LavineD., and KanalL. N., Distributed architecture and parallel non-directional search for knowledge based cartographic feature extraction, Int. J. Man-Machine Studies 20, 107, (1984).
Nii, P. H., Feigenbaum, E. A., and Anton, J. J., Signal-to-symbol transformation, HASP/SIAP case study, AI Magazine, Spring 1982, 23.
PauL., Fusion of multisensor data in pattern recognition, in Pattern Recognition Theory and Applications (eds. J.Kittler, K. S.Fu, L.Pau) D. Reidel, Dordrecht (1981).
Smith, R. G., (1985), Report on the 1984 Distributed artifical intelligence workshop, AI Magazine, Fall 1985, 234.
PauL., Multisensor fusion for vision using artificial intelligence, in Digital Image Processing in Industrial Applications (ed. G.Ollus) IFAC Proc., Pergamon Press, London (1987).
Lajeunesse, T. J., Sensor fusion, Defence Science & Engineering, Sept. 1986, 21.
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Pau, L.F. Sensor data fusion. Journal of Intelligent and Robotic Systems 1, 103–116 (1988). https://doi.org/10.1007/BF00348718
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DOI: https://doi.org/10.1007/BF00348718